Enhanced integrated positioning method and system thereof for vehicle

• US 6,246,960 B1
• Filed: 03/26/1999
• Issued: 06/12/2001
• Est. Priority Date: 11/06/1998
• Status: Expired due to Term

• Current Assignee: American GNC Corporation
• Original Assignee: Ching-Fang Lin
• Inventors: Lin, Ching-Fang
• Primary Examiner(s): Lobo, Ian J.
• Application Number:
  US09/277,323
• Time in Patent Office: 809 Days
• Field of Search: 701/200, 701/207, 701/213, 701/214, 701/220, 342/357.01, 342/357.05, 342/357.06
• US Class Current: 701/214
• CPC Class Codes: G01C 21/1652 with ranging devices, e.g. LIDAR or RADAR
• CPC Class Codes: G01C 21/188 for accumulated errors, e.g. by coupling inertial systems with absolute positioning systems

Abstract

An enhanced positioning method and system with altitude measurement includes the steps of receiving the inertial measurements from an inertial sensor, the global positioning system raw measurements from a global positioning system processor, and the altitude measurement from an altitude measurement device and performing integrated filtering, feeding the velocity and acceleration back to the global positioning system satellite signal tracking loops, and using integration solution to aid the global positioning system satellite signal carrier phase ambiguity resolution. The present invention provides a positioning method and system with high accuracy and robustness. The global positioning system measurements assure the long term positioning accuracy and the inertial measurements assure the short term positioning accuracy. The altitude measurement improves the vertical positioning accuracy. The velocity and acceleration from the inertial device aid the global positioning system signal tracking. The integrated positioning solution is employed to derive the global positioning system carrier phase ambiguity number. The present patent supports high precision navigation in general aviation and space applications. It also supports high precision approach and landing for aircraft, reusable launch vehicles, and other air transportation vehicles.

Claims

1. An enhanced integrated positioning method, comprising the steps of:

(a) receiving a plurality of global positioning system satellite signals by a GPS processor to derive position and velocity information of a vehicle and a plurality of global positioning system (GPS) raw measurements, including pseudorange, carrier phase, and Doppler shift;

(b) sending said GPS raw measurements to a central navigation processor from said GPS processor;

(c) receiving a plurality of inertial measurements including body angular rates and specific forces from an inertial measurement unit (IMU);

(d) sending said inertial measurements from said IMU to an inertial navigation system (INS) processor of said central navigation processor for computing an inertial navigation solution, including position, velocity, acceleration, and attitude of said vehicle;

(e) receiving a vehicle altitude measurement from an altitude measurement device;

(f) blending an inertial navigation solution derived from said INS processor, said GPS raw measurements from said GPS processor and said vehicle altitude measurement from said altitude measurement device in a robust Kalman filter to derive a plurality of INS corrections and GPS corrections;

(g) feeding back said INS corrections from said robust Kalman filter to said INS processor to correct said inertial navigation solution;

(h) injecting said velocity and acceleration of said vehicle from said INS processor into a micro-processor of said GPS processor to aid a plurality of global positioning system code tracking loops and a plurality of global positioning system carrier phase tracking loops for requiring and tracking said global positioning system satellite signals, wherein said micro-processor of said GPS processor outputs said GPS raw measurements including said pseudorange, said carrier phase, and said Doppler shift;

(i) injecting said GPS raw measurements from said micro-processor of said GPS processor, said inertial navigation solution from said INS processor, and said inertial corrections and said GPS corrections from said robust Kalman filter into a carrier phase integer ambiguity resolution module to fix a plurality of global positioning system satellite signal carrier phase integer ambiguity numbers;

(j) sending said global positioning system satellite signal carrier phase integer numbers from said carrier phase integer ambiguity resolution module to said robust Kalman filter to derive a further improved vehicle navigation solution; and

(k) sending said inertial navigation solution from said INS processor to an I/O interface, so as to provide navigation data for an on-board avionics system.

2. An enhanced integrated positioning method, as recited in claim 1, wherein said robust Kalman filter comprises a GPS error compensation module for gathering said pseudorange, carrier phase, and Doppler frequency of said GPS measurements from said GPS processor, and said position and velocity corrections from an updating state vector module to perform GPS error compensation to form corrected GPS raw data, including pseudorange, carrier phase, and Doppler frequency, which are sent to a preprocessing module, wherein said preprocessing module receives GPS satellite ephemeris from said GPS processor said corrected GPS raw data from said GPS error compensation module, said vehicle altitude measurement from said altitude measurement device, and INS solutions from said INS processor, said preprocessing module performing calculation of state transit matrix and sending with said state vector to a state vector prediction module, wherein said calculated state transit matrix is also sent to a covariance propagation module which calculates a measurement matrix and a current measurement vector according to a computed measurement matrix and a measurement model, and that said measurement matrix and said computed current measurement vector are passed to a computing measurement residue module, said state vector prediction module receiving said state transit matrix and said state vector from said preprocessing module to perform state prediction of current epoch, said predicted current state vector being passed to said computing measurement residue module which receives predicted current state vector from said state vector prediction module and said measurement matrix and said current measurement vector from said preprocessing module, wherein said computing measurement residue module calculates measurement residues by subtracting said multiplication of said measurement matrix and said predicted current state vector from said current measurement vector, and said measurement residues are sent to a residue monitor module and said updating state vector module, wherein said residue monitor module performs a discrimination on said measurement residues received from said computing measurement residue module, wherein said covariance propagation module gathers covariance of system process from said residue monitor module, said state transit matrix from said preprocessing module, and covariance of estimated error to calculate current covariance of said estimated error which is sent to a computing optimal gain module, wherein said computing optimal gain module receives said current covariance of said estimated error from said covariance computing module to compute optimal gain which is passed to a covariance updating module and said updating state vector module, said covariance updating module updating said covariance of said estimated error and sending to said covariance propagation module, wherein said updating state vector module receives said optimal gain from said computing optimal gain module and said measurement residues from said computing measurement residue module, said updating state vector calculating said current estimate of state vector including position, velocity and attitude errors and sending to said GPS error compensation module and said INS processor.

3. An enhanced integrated positioning system, comprising:

a global positioning system (GPS) processor for providing location related information;

an inertial measurement unit (IMU) for providing inertial measurements including body angular rates and specific forces;

an altitude measurement generator for providing vehicle altitude measurement, wherein said altitude measurement generator is an altitude measurement device for providing an altitude measurement above mean sea level (MSL);

a central navigation processor, which is connected with said GPS processor, said IMU and said altitude measurement device, for fusing said location related information from said GPS processor, said inertial measurements from said IMU and said altitude measurement from said altitude measurement generator to produce navigation data of a platform, including position, velocity and attitude of said platform; and

an input/output (I/O) interface, which is connected to said central navigation processor, for outputting said navigation data;

wherein said GPS processor produces a plurality of pseudorange, carrier phase, and Doppler shift;

wherein said central navigation processor comprising an inertial navigation system (INS) processor, a Kalman filter, and a carrier phase integer ambiguity resolution module;

wherein said pseudorange, carrier phase and Doppler shift are passed to said central navigation processor, said altitude measurement above MSL is passed to said Kalman filter, and said inertial measurements are injected into said inertial navigation system (INS) processor;

wherein outputs of said INS processor, said altitude measurement above MSL and said pseudorange, carrier phase, and Doppler shift are blended in said Kalman filter, and an output of said Kalman filter is fed back to said INS processor to correct an INS navigation solution outputting from said central navigation processor to said I/O interface;

wherein said INS processor provides velocity and acceleration data injecting into a micro-processor of said GPS processor to aid code and carrier phase tracking of GPS satellite signals;

wherein outputs of said micro-processor of said GPS processor, said INS processor and said Kalman filter are injected into said carrier phase integer ambiguity resolution module to fix global positioning system satellite signal carrier phase integer ambiguity number;

wherein said carrier phase integer ambiguity resolution module outputs carrier phase integer number into said Kalman filter to further improve positioning accuracy;

wherein said INS processor outputs navigation data to said I/O interface;

wherein said microprocessor of said GPS processor outputs said pseudorange, carrier phase, and Doppler shift, global positioning system satellite ephemeris, and atmosphere parameters to said Kalman filter;

wherein said INS processor processes said inertial measurements, which are body angular rates and specific forces, and said position error, velocity error, and attitude error coming from said Kalman filter to derive said corrected navigation solution;

wherein said altitude measurement device sends said altitude measurement above MSL to said Kalman filter.

4. An enhanced integrated positioning system, as recited in claim 3, wherein said INS processor comprises an IMU I/O interface, an IMU error compensation module, a coordinate transformation computation module, an attitude position velocity computation module, a transformation matrix computation module, and an earth and vehicle rate computation module, wherein said IMU I/O interface collects said signal of said body angular rates and specific forces from said IMU for processing and converting to digital data which are corrupted by said inertial sensor measurement errors to form contaminated data that are passed to said IMU error compensation module, wherein said IMU error compensation module receives sensor error estimates derived from said Kalman filter to perform IMU error mitigation on said IMU data, said corrected inertial data being sent to said coordinate transformation computation module and said transformation matrix computation module, where said body angular rates are sent to said transformation matrix computation module and said specific forces are sent said coordinate transformation computation module, wherein said transformation matrix computation module receives said body angular rates from said IMU error computation module and an earth and vehicle rate from said earth and vehicle rate computation module to perform transformation matrix computation, said transformation matrix computation module sending said transformation matrix to said coordinate transformation computation module and attitude position velocity computation module, an attitude update algorithm in said transformation matrix computation module using said quaternion method because of its advantageous numerical and stability characteristics, wherein said coordinate transformation module collects said specific forces from said IMU error computation module and said transformation matrix from said transformation matrix computation module to perform said coordinate transformation, said coordinate transformation computation sending said specific forces transferred into said coordinate system presented by said transformation matrix to said attitude position velocity computation module, wherein said attitude position velocity computation module receives said transformed specific forces from said coordinate transformation computation module and said transformation matrix from said transformation matrix computation module to perform said attitude, position, velocity update.

5. An enhanced integrated positioning system, as recited in claim 4, wherein after computation of said position and velocity, said position and velocity errors calculated by said Kalman filter are used in said attitude position velocity computation module to correct said inertial solution.

6. An enhanced integrated positioning system, as recited in claim 5, wherein said attitude errors computed by said Kalman filter is sent to said attitude position velocity computation module to perform attitude correction in said attitude position velocity computation module.

7. An enhanced integrated positioning system, as recited in claim 5, wherein said attitude errors computed by said Kalman filter is sent to said transformation matrix computation module to perform said attitude correction before said attitude position velocity computation module.

8. An enhanced integrated positioning system, as recited in claim 6, wherein the corrected inertial solution obtained from said attitude position velocity computation module is passed to said Kalman filter to construct said measurements of said Kalman filter, moreover the corrected inertial navigation solution is also send to said carrier phase integer ambiguity resolution module to aid said global positioning system satellite carrier phase integer ambiguity fixing, and that the corrected velocity and accelerate is passed to microprocessor of said GPS processor to aid said global positioning system satellite signal carrier phase and code tracking, wherein attitude, position, and velocity computed by said attitude position velocity computation module are sent to said earth and vehicle rate computation module to calculate an Earth rotation rate and a vehicle rotation rate which are sent to said transformation matrix computation module, wherein said attitude, position, and velocity information is send to said I/O interface which provides a navigation data source.

9. An enhanced integrated positioning system, as recited in claim 7, wherein the corrected inertial solution obtained from said attitude position velocity computation module is passed to said Kalman filter to construct said measurements of said Kalman filter, moreover the corrected inertial navigation solution is also send to said carrier phase integer ambiguity resolution module to aid said global positioning system satellite carrier phase integer ambiguity fixing, and that the corrected velocity and accelerate is passed to microprocessor of said GPS processor to aid said global positioning system satellite signal carrier phase and code tracking, wherein attitude, position, and velocity computed by said attitude position velocity computation module are sent to said earth and vehicle rate computation module to calculate an Earth rotation rate and a vehicle rotation rate which are sent to said transformation matrix computation module, wherein said attitude, position, and velocity information is sent to said I/O interface which provides a navigation data source.

10. An enhanced integrated positioning system, as recited in claim 8 or 9, wherein said Kalman filter is a robust Kalman filter for providing near-optimal performance over a large class of process and measurement models and for blending GPS measurements and said inertial sensor measurements;

wherein said robust Kalman filter comprises a GPS error compensation module for gathering said pseudorange, carrier phase, and Doppler frequency of said GPS measurements from said GPS processor, and said position and velocity corrections from an updating state vector module to perform GPS error compensation to form corrected GPS raw data, including pseudorange, carrier phase, and Doppler frequency, which are sent to a preprocessing module, wherein said preprocessing module receives GPS satellite ephemeris from said GPS processor said corrected GPS raw data from said GPS error compensation module, said vehicle altitude measurement from said altitude measurement device, and INS solutions from said INS processor, said preprocessing module performing calculation of state transit matrix and sending with said state vector to a state vector prediction module, wherein said calculated state transit matrix is also sent to a covariance propagation module which calculates a measurement matrix and a current measurement vector according to a computed measurement matrix and a measurement model, and that said measurement matrix and said computed current measurement vector are passed to a computing measurement residue module, said state vector prediction module receiving said state transit matrix and said state vector from said preprocessing module to perform state prediction of current epoch, said predicted current state vector being passed to said computing measurement residue module which receives predicted current state vector from said state vector prediction module and said measurement matrix and said current measurement vector from said preprocessing module, wherein said computing measurement residue module calculates measurement residues by subtracting said multiplication of said measurement matrix and said predicted current state vector from said current measurement vector, and said measurement residues are sent to a residue monitor module and said updating state vector module, wherein said residue monitor module performs a discrimination on said measurement residues received from said computing measurement residue module, wherein said covariance propagation module gathers covariance of system process from said residue monitor module, said state transit matrix from said preprocessing module, and covariance of estimated error to calculate current covariance of said estimated error which is sent to a computing optimal gain module, wherein said computing optimal gain module receives said current covariance of said estimated error from said covariance computing module to compute optimal gain which is passed to a covariance updating module and said updating state vector module, said covariance updating module updating said covariance of said estimated error and sending to said covariance propagation module, wherein said updating state vector module receives said optimal gain from said computing optimal gain module and said measurement residues from said computing measurement residue module, said updating state vector calculating said current estimate of state vector including position, velocity and attitude errors and sending to said GPS error compensation module and said INS processor.

11. An enhanced integrated positioning system, as recited in claim 8 or 9, wherein said carrier phase integer ambiguity resolution module collects position and velocity data from said INS processor, said carrier phase and Doppler shift measurement from said microprocessor of said GPS processor, and covariance matrix from said Kalman filter to fix said global positioning system satellite signal integer ambiguity number, wherein after fixing of carrier phase ambiguities, said carrier phase ambiguity number is passed to said Kalman filter to further improve said measurement accuracy of said global positioning system raw data.

12. An enhanced integrated positioning system, as recited in claim 11, wherein said carrier phase integer ambiguity resolution module comprises a geometry distance computation module, a least square adjustment module, a satellite clock model, an ionospheric model, a tropospheric model, a satellite prediction module, and a search space determination module, wherein said satellite prediction module collects ephemeris of visible global positioning system satellites from said GPS processor to perform satellite position calculation, a predicted satellite position is passed to said geometry distance computation module which receives a vehicle'"'"'s precision position information from said INS processor and computes a geometrical distance between a satellite and a vehicle that is sent to said least square adjustment module, wherein said tropospheric model collects a time tag from said GPS processor and calculates a tropospheric delay of said global positioning system satellite signal using said embedded tropospheric delay model, in which said calculated troposheric delay is sent to said least square adjustment module, besides said ionospheric model collects said time tag and ionospheric parameters broadcast by said global positioning system satellite from said GPS processor, so that said ionospheric model calculates a minus time delay introduced by said ionosphere that is sent to said least square adjustment module, moreover said satellite clock model collects global positioning system satellite clock parameters to perform satellite clock correction calculation, in which said satellite clock correction is also sent to said least square adjustment module, and that said search space determination module receives covariance matrix of said measurement vector from said Kalman filter, so that based on said covariance matrix, said search space determination module derives said measurement error and determines said global positioning system satellite carrier phase integer ambiguity search space which is sent to said least square adjustment module, wherein said least square adjustment module gathers said geometrical distance from said vehicle to said global positioning system satellite from said geometry distance computation module, said tropospheric delay from said tropospheric model, said ionospheric delay from said ionospheric model, and said satellite clock correction from said satellite clock model to calculate an initial search origin, said least square adjustment module also receiving a search space from said search space determination module wherein a standard least square adjustment algorithm is applied to said initial search origin and said search space to fix said carrier phase ambiguity.

13. An enhanced integrated positioning system, comprising:

a global positioning system (GPS) processor for providing location related information;

an inertial measurement unit (IMU) for providing inertial measurements including body angular rates and specific forces;

an altitude measurement generator for providing vehicle altitude measurement, wherein said altitude measurement generator is a radar altimeter for providing an altitude measurement above a terrain;

a central navigation processor, which is connected with said GPS processor, said IMU and said altitude measurement device, for fusing said location related information from said GPS processor, said inertial measurements from said IMU and said altitude measurement from said altitude measurement generator to produce navigation data of a platform, including position, velocity and attitude of said platform; and

an input/output (I/O) interface, which is connected to said central navigation processor, for outputting said navigation data;

wherein said GPS processor produces a plurality of pseudorange, carrier phase, and Doppler shift;

wherein said central navigation processor comprising an inertial navigation system (INS) processor, a data fusion module, a terrain database, a Kalman filter, and a carrier phase integer ambiguity resolution module;

wherein said pseudorange, carrier phase and Doppler shift are passed to said central navigation processor, said altitude measurement above terrain is passed to said data fusion module, and said inertial measurements are injected into said inertial navigation system (INS) processor;

wherein outputs of said INS processor, output of said data fusion module and said pseudorange, carrier phase, and Doppler shift are blended in said Kalman filter, and an output of said Kalman filter is fed back to said INS processor to correct an INS navigation solution outputting from said central navigation processor to said I/O interface;

wherein said INS processor provides velocity and acceleration data injecting into a micro-processor of said GPS processor to aid code and carrier phase tracking of GPS satellite signals;

wherein outputs of said micro-processor of said GPS processor, said INS processor and said Kalman filter are injected into said carrier phase integer ambiguity resolution module to fix global positioning system satellite signal carrier phase integer ambiguity number;

wherein said carrier phase integer ambiguity resolution module outputs carrier phase integer number into said Kalman filter to further improve positioning accuracy;

wherein said INS processor outputs navigation data to said I/O interface;

wherein said microprocessor of said GPS processor outputs said pseudorange, carrier phase, and Doppler shift, global positioning system satellite ephemeris, and atmosphere parameters to said Kalman filter;

wherein said INS processor processes said inertial measurements, which are body angular rates and specific forces, and said position error, velocity error, and attitude error coming from said Kalman filter to derive said corrected navigation solution;

wherein said radar altimeter sends vehicle altitude measurement to said data fusion module, said INS processor sends said vehicle position information to said terrain database, said terrain database performs database query to derive a terrain height above the mean sea level and sends said terrain height to said data fusion module, said data fusion module receives said vehicle altitude measurement above terrain from said radar altimeter and said terrain height from said terrain database to derive a vehicle altitude above mean sea level, said vehicle altitude above mean sea level is sent to said Kalman filter.

14. An enhanced integrated positioning system, as recited in claim 13, wherein said INS processor comprises an IMU I/O interface, an IMU error compensation module, a coordinate transformation computation module, an attitude position velocity computation module, a transformation matrix computation module, and an earth and vehicle rate computation module, wherein said IMU I/O interface collects said signal of said body angular rates and specific forces from said IMU for processing and converting to digital data which are corrupted by said inertial sensor measurement errors to form contaminated data that are passed to said IMU error compensation module, wherein

said IMU error compensation module receives sensor error estimates derived from said Kalman filter to perform IMU error mitigation on said IMU data, said corrected inertial data being sent to said coordinate transformation computation module and said transformation matrix computation module, where said body angular rates are sent to said transformation matrix computation module and said specific forces are sent said coordinate transformation computation module, wherein said transformation matrix computation module receives said body angular rates from said IMU error computation module and an earth and vehicle rate from said earth and vehicle rate computation module to perform transformation matrix computation, said transformation matrix computation module sending said transformation matrix to said coordinate transformation computation module and attitude position velocity computation module, an attitude update algorithm in said transformation matrix computation module using said quaternion method because of its advantageous numerical and stability characteristics, wherein said coordinate transformation module collects said specific forces from said IMU error computation module and said transformation matrix from said transformation matrix computation module to perform said coordinate transformation, said coordinate transformation computation sending said specific forces transferred into said coordinate system presented by said transformation matrix to said attitude position velocity computation module, wherein said attitude position velocity computation module receives said transformed specific forces from said coordinate transformation computation module and said transformation matrix from said transformation matrix computation module to perform said attitude, position, velocity update.

15. An enhanced integrated positioning system, as recited in claim 14, wherein after computation of said position and velocity, said position and velocity errors calculated by said Kalman filter are used in said attitude position velocity computation module to correct said inertial solution.

16. An enhanced integrated positioning system, as recited in claim 15, wherein said attitude errors computed by said Kalman filter is sent to said attitude position velocity computation module to perform attitude correction in said attitude position velocity computation module.

17. An enhanced integrated positioning system, as recited in claim 15, wherein said attitude errors computed by said Kalman filter is sent to said transformation matrix computation module to perform said attitude correction before said attitude position velocity computation module.

18. An enhanced integrated positioning system, as recited in claim 16, wherein the corrected inertial solution obtained from said attitude position velocity computation module is passed to said Kalman filter to construct said measurements of said Kalman filter, moreover the corrected inertial navigation solution is also sent to said carrier phase integer ambiguity resolution module to aid said global positioning system satellite carrier phase integer ambiguity fixing, and that the corrected velocity and accelerate is passed to microprocessor of said GPS processor to aid said global positioning system satellite signal carrier phase and code tracking, wherein attitude, position, and velocity computed by said attitude position velocity computation module are sent to said earth and vehicle rate computation module to calculate an Earth rotation rate and a vehicle rotation rate which are sent to said transformation matrix computation module, wherein said attitude, position, and velocity information is send to said I/O interface which provides a navigation data source.

19. An enhanced integrated positioning system, as recited in claim 17, wherein the corrected inertial solution obtained from said attitude position velocity computation module is passed to said Kalman filter to construct said measurements of said Kalman filter, moreover the corrected inertial navigation solution is also send to said carrier phase integer ambiguity resolution module to aid said global positioning system satellite carrier phase integer ambiguity fixing, and that the corrected velocity and accelerate is passed to microprocessor of said GPS processor to aid said global positioning system satellite signal carrier phase and code tracking, wherein attitude, position, and velocity computed by said attitude position velocity computation module are sent to said earth and vehicle rate computation module to calculate an Earth rotation rate and a vehicle rotation rate which are sent to said transformation matrix computation module, wherein said attitude, position, and velocity information is sent to said I/O interface which provides a navigation data source.

20. An enhanced integrated positioning system, as recited in claim 18 or 19, wherein said Kalman filter is a robust Kalman filter for providing near-optimal performance over a large class of process and measurement models and for blending GPS measurements and said inertial sensor measurements;

wherein said robust Kalman filter comprises a GPS error compensation module for gathering said pseudorange, carrier phase, and Doppler frequency of said GPS measurements from said GPS processor, and said position and velocity corrections from an updating state vector module to perform GPS error compensation to form corrected GPS raw data, including pseudorange, carrier phase, and Doppler frequency, which are sent to a preprocessing module, wherein said preprocessing module receives GPS satellite ephemeris from said GPS processor said corrected GPS raw data from said GPS error compensation module, said vehicle altitude measurement from said altitude measurement device, and INS solutions from said INS processor, said preprocessing module performing calculation of state transit matrix and sending with said state vector to a state vector prediction module, wherein said calculated state transit matrix is also sent to a covariance propagation module which calculates a measurement matrix and a current measurement vector according to a computed measurement matrix and a measurement model, and that said measurement matrix and said computed current measurement vector are passed to a computing measurement residue module, said state vector prediction module receiving said state transit matrix and said state vector from said preprocessing module to perform state prediction of current epoch, said predicted current state vector being passed to said computing measurement residue module which receives predicted current state vector from said state vector prediction module and said measurement matrix and said current measurement vector from said preprocessing module, wherein said computing measurement residue module calculates measurement residues by subtracting said multiplication of said measurement matrix and said predicted current state vector from said current measurement vector, and said measurement residues are sent to a residue monitor module and said updating state vector module, wherein said residue monitor module performs a discrimination on said measurement residues received from said computing measurement residue module, wherein said covariance propagation module gathers covariance of system process from said residue monitor module, said state transit matrix from said preprocessing module, and covariance of estimated error to calculate current covariance of said estimated error which is sent to a computing optimal gain module, wherein said computing optimal gain module receives said current covariance of said estimated error from said covariance computing module to compute optimal gain which is passed to a covariance updating module and said updating state vector module, said covariance updating module updating said covariance of said estimated error and sending to said covariance propagation module, wherein said updating state vector module receives said optimal gain from said computing optimal gain module and said measurement residues from said computing measurement residue module, said updating state vector calculating said current estimate of state vector including position, velocity and attitude errors and sending to said GPS error compensation module and said INS processor.

21. An enhanced integrated positioning system, as recited in claim 18 or 19, wherein said carrier phase integer ambiguity resolution module collects position and velocity data from said INS processor, said carrier phase and Doppler shift measurement from said microprocessor of said GPS processor, and covariance matrix from said Kalman filter to fix said global positioning system satellite signal integer ambiguity number, wherein after fixing of carrier phase ambiguities, said carrier phase ambiguity number is passed to said Kalman filter to further improve said measurement accuracy of said global positioning system raw data.

22. An enhanced integrated positioning system, as recited in claim 21, wherein said carrier phase integer ambiguity resolution module comprises a geometry distance computation module, a least square adjustment module, a satellite clock model, an ionospheric model, a tropospheric model, a satellite prediction module, and a search space determination module, wherein said satellite prediction module collects ephemeris of visible global positioning system satellites from said GPS processor to perform satellite position calculation, a predicted satellite position is passed to said geometry distance computation module which receives a vehicle'"'"'s precision position information from said INS processor and computes a geometrical distance between a satellite and a vehicle that is sent to said least square adjustment module, wherein said tropospheric model collects a time tag from said GPS processor and calculates a tropospheric delay of said global positioning system satellite signal using said embedded tropospheric delay model, in which said calculated troposheric delay is sent to said least square adjustment module, besides said ionospheric model collects said time tag and ionospheric parameters broadcast by said global positioning system satellite from said GPS processor, so that said ionospheric model calculates a minus time delay introduced by said ionosphere that is sent to said least square adjustment module, moreover said satellite clock model collects global positioning system satellite clock parameters to perform satellite clock correction calculation, in which said satellite clock correction is also sent to said least square adjustment module, and that said search space determination module receives covariance matrix of said measurement vector from said Kalman filter, so that based on said covariance matrix, said search space determination module derives said measurement error and determines said global positioning system satellite carrier phase integer ambiguity search space which is sent to said least square adjustment module, wherein said least square adjustment module gathers said geometrical distance from said vehicle to said global positioning system satellite from said geometry distance computation module, said tropospheric delay from said tropospheric model, said ionospheric delay from said ionospheric model, and said satellite clock correction from said satellite clock model to calculate an initial search origin, said least square adjustment module also receiving a search space from said search space determination module wherein a standard least square adjustment algorithm is applied to said initial search origin and said search space to fix said carrier phase ambiguity.

23. An enhanced integrated positioning system, comprising:

a global positioning system (GPS) processor for providing location related information;

an inertial measurement unit (IMU) for providing inertial measurements including body angular rates and specific forces;

an altitude measurement generator for providing vehicle altitude measurement, wherein said altitude measurement generator is an altitude measurement device for providing an altitude measurement above mean sea level (MSL);

a central navigation processor, which is connected with said GPS processor, said IMU and said altitude measurement device, for fusing said location related information from said GPS processor, said inertial measurements from said IMU and said altitude measurement from said altitude measurement generator to produce navigation data of a platform, including position, velocity and attitude of said platform; and

an input/output (I/O) interface, which is connected to said central navigation processor, for outputting said navigation data;

wherein said GPS processor produces a plurality of pseudorange and Doppler shift;

wherein said central navigation processor comprising an inertial navigation system (INS) processor and a Kalman filter;

wherein said pseudorange and Doppler shift are passed to said central navigation processor, said altitude measurement above MSL is passed to said Kalman filter, and said inertial measurements are injected into said inertial navigation system (INS) processor;

wherein outputs of said INS processor, said altitude measurement above MSL and said pseudorange and Doppler shift are blended in said Kalman filter, and an output of said Kalman filter is fed back to said INS processor to correct an INS navigation solution outputting from said central navigation processor to said I/O interface;

wherein said INS processor provides velocity and acceleration data injecting into a micro-processor of said GPS processor to aid code tracking of GPS satellite signals;

wherein said INS processor outputs navigation data to said I/O interface;

wherein said microprocessor of said GPS processor outputs said pseudorange and Doppler shifts, global positioning system satellite ephemeris, and atmosphere parameters to said Kalman filter;

wherein said INS processor processes said inertial measurements, which are body angular rates and specific forces, and said position error, velocity error, and attitude error coming from said Kalman filter to derive said corrected navigation solution;

wherein said altitude measurement device sends said altitude measurement above MSL to said Kalman filter.

24. An enhanced integrated positioning system, as recited in claim 23, wherein said INS processor comprises an IMU I/O interface, an IMU error compensation module, a coordinate transformation computation module, an attitude position velocity computation module, a transformation matrix computation module, and an earth and vehicle rate computation module, wherein said IMU I/O interface collects said signal of said body angular rates and specific forces from said IMU for processing and converting to digital data which are corrupted by said inertial sensor measurement errors to form contaminated data that are passed to said IMU error compensation module, wherein said IMU error compensation module receives sensor error estimates derived from said Kalman filter to perform IMU error mitigation on said IMU data, said corrected inertial data being sent to said coordinate transformation computation module and said transformation matrix computation module, where said body angular rates are sent to said transformation matrix computation module and said specific forces are sent said coordinate transformation computation module, wherein said transformation matrix computation module receives said body angular rates from said IMU error computation module and an earth and vehicle rate from said earth and vehicle rate computation module to perform transformation matrix computation, said transformation matrix computation module sending said transformation matrix to said coordinate transformation computation module and attitude position velocity computation module, an attitude update algorithm in said transformation matrix computation module using said quaternion method because of its advantageous numerical and stability characteristics, wherein said coordinate transformation module collects said specific forces from said IMU error computation module and said transformation matrix from said transformation matrix computation module to perform said coordinate transformation, said coordinate transformation computation sending said specific forces transferred into said coordinate system presented by said transformation matrix to said attitude position velocity computation module, wherein said attitude position velocity computation module receives said transformed specific forces from said coordinate transformation computation module and said transformation matrix from said transformation matrix computation module to perform said attitude, position, velocity update.

25. An enhanced integrated positioning system, as recited in claim 24, wherein after computation of said position and velocity, said position and velocity errors calculated by said Kalman filter are used in said attitude position velocity computation module to correct said inertial solution.

26. An enhanced integrated positioning system, as recited in claim 25, wherein said attitude errors computed by said Kalman filter is sent to said attitude position velocity computation module to perform attitude correction in said attitude position velocity computation module.

27. An enhanced integrated positioning system, as recited in claim 25, wherein said attitude errors computed by said Kalman filter is sent to said transformation matrix computation module to perform said attitude correction before said attitude position velocity computation module.

28. An enhanced integrated positioning system, as recited in claim 25, 26 or 27, wherein the corrected inertial solution obtained from said attitude position velocity computation module is passed to said Kalman filter to construct said measurements of said Kalman filter, moreover the corrected inertial navigation solution is also send to said carrier phase integer ambiguity resolution module to aid said global positioning system satellite carrier phase integer ambiguity fixing, and that the corrected velocity and accelerate is passed to microprocessor of said GPS processor to aid said global positioning system satellite signal carrier phase and code tracking, wherein attitude, position, and velocity computed by said attitude position velocity computation module are sent to said earth and vehicle rate computation module to calculate an Earth rotation rate and a vehicle rotation rate which are sent to said transformation matrix computation module, wherein said attitude, position, and velocity information is sent to said I/O interface which provides a navigation data source.

29. An enhanced integrated positioning system, as recited in claim 28, wherein said Kalman filter is a robust Kalman filter for providing near-optimal performance over a large class of process and measurement models and for blending GPS measurements and said inertial sensor measurements;

wherein said robust Kalman filter comprises a GPS error compensation module for gathering said pseudorange, carrier phase, and Doppler frequency of said GPS measurements from said GPS processor, and said position and velocity corrections from an updating state vector module to perform GPS error compensation to form corrected GPS raw data, including pseudorange, carrier phase, and Doppler frequency, which are sent to a preprocessing module, wherein said preprocessing module receives GPS satellite ephemeris from said GPS processor said corrected GPS raw data from said GPS error compensation module, said vehicle altitude measurement from said altitude measurement device, and INS solutions from said INS processor, said preprocessing module performing calculation of state transit matrix and sending with said state vector to a state vector prediction module, wherein said calculated state transit matrix is also sent to a covariance propagation module which calculates a measurement matrix and a current measurement vector according to a computed measurement matrix and a measurement model, and that said measurement matrix and said computed current measurement vector are passed to a computing measurement residue module, said state vector prediction module receiving said state transit matrix and said state vector from said preprocessing module to perform state prediction of current epoch, said predicted current state vector being passed to said computing measurement residue module which receives predicted current state vector from said state vector prediction module and said measurement matrix and said current measurement vector from said preprocessing module, wherein said computing measurement residue module calculates measurement residues by subtracting said multiplication of said measurement matrix and said predicted current state vector from said current measurement vector, and said measurement residues are sent to a residue monitor module and said updating state vector module, wherein said residue monitor module performs a discrimination on said measurement residues received from said computing measurement residue module, wherein said covariance propagation module gathers covariance of system process from said residue monitor module, said state transit matrix from said preprocessing module, and covariance of estimated error to calculate current covariance of said estimated error which is sent to a computing optimal gain module, wherein said computing optimal gain module receives said current covariance of said estimated error from said covariance computing module to compute optimal gain which is passed to a covariance updating module and said updating state vector module, said covariance updating module updating said covariance of said estimated error and sending to said covariance propagation module, wherein said updating state vector module receives said optimal gain from said computing optimal gain module and said measurement residues from said computing measurement residue module, said updating state vector calculating said current estimate of state vector including position, velocity and attitude errors and sending to said GPS error compensation module and said INS processor.

30. An enhanced integrated positioning system, comprising:

a global positioning system (GPS) processor for providing location related information;

an inertial measurement unit (IMU) for providing inertial measurements including body angular rates and specific forces;

an altitude measurement generator for providing vehicle altitude measurement, wherein said altitude measurement generator is a radar altimeter for providing an altitude measurement above a terrain;

a central navigation processor, which is connected with said GPS processor, said IMU and said altitude measurement device, for fusing said location related information from said GPS processor, said inertial measurements from said IMU and said altitude measurement from said altitude measurement generator to produce navigation data of a platform, including position, velocity and attitude of said platform; and

an input/output (I/O) interface, which is connected to said central navigation processor, for outputting said navigation data;

wherein said GPS processor produces a plurality of pseudorange and Doppler shift;

wherein said central navigation processor comprising an inertial navigation system (INS) processor and a Kalman filter;

wherein said pseudorange and Doppler shift are passed to said central navigation processor, said altitude measurement above terrain is passed to said data fusion module, and said inertial measurements are injected into said inertial navigation system (INS) processor;

wherein outputs of said INS processor, output of said data fusion module and said pseudorange and Doppler shift are blended in said Kalman filter, and an output of said Kalman filter is fed back to said INS processor to correct an INS navigation solution outputting from said central navigation processor to said I/O interface;

wherein said INS processor provides velocity and acceleration data injecting into a micro-processor of said GPS processor to aid code tracking of GPS satellite signals;

wherein said INS processor outputs navigation data to said I/O interface;

wherein said microprocessor of said GPS processor outputs said pseudorange and Doppler shifts, global positioning system satellite ephemeris, and atmosphere parameters to said Kalman filter;

wherein said INS processor processes said inertial measurements, which are body angular rates and specific forces, and said position error, velocity error, and attitude error coming from said Kalman filter to derive said corrected navigation solution;

wherein said radar altimeter sends vehicle altitude measurement to said data fusion module, said INS processor sends said vehicle position information to said terrain database, said terrain database performs database query to derive a terrain height above the mean sea level and sends said terrain height to said data fusion module, said data fusion module receives said vehicle altitude measurement above terrain from said radar altimeter and said terrain height from said terrain database to derive a vehicle altitude above mean sea level, said vehicle altitude above mean sea level is sent to said Kalman filter.

31. An enhanced integrated positioning system, as recited in claim 30, wherein said INS processor comprises an IMU I/O interface, an IMU error compensation module, a coordinate transformation computation module, an attitude position velocity computation module, a transformation matrix computation module, and an earth and vehicle rate computation module, wherein said IMU I/O interface collects said signal of said body angular rates and specific forces from said IMU for processing and converting to digital data which are corrupted by said inertial sensor measurement errors to form contaminated data that are passed to said IMU error compensation module, wherein said IMU error compensation module receives sensor error estimates derived from said Kalman filter to perform IMU error mitigation on said IMU data, said corrected inertial data being sent to said coordinate transformation computation module and said transformation matrix computation module, where said body angular rates are sent to said transformation matrix computation module and said specific forces are sent said coordinate transformation computation module, wherein said transformation matrix computation module receives said body angular rates from said IMU error computation module and an earth and vehicle rate from said earth and vehicle rate computation module to perform transformation matrix computation, said transformation matrix computation module sending said transformation matrix to said coordinate transformation computation module and attitude position velocity computation module, an attitude update algorithm in said transformation matrix computation module using said quaternion method because of its advantageous numerical and stability characteristics, wherein said coordinate transformation module collects said specific forces from said IMU error computation module and said transformation matrix from said transformation matrix computation module to perform said coordinate transformation, said coordinate transformation computation sending said specific forces transferred into said coordinate system presented by said transformation matrix to said attitude position velocity computation module, wherein said attitude position velocity computation module receives said transformed specific forces from said coordinate transformation computation module and said transformation matrix from said transformation matrix computation module to perform said attitude, position, velocity update.

32. An enhanced integrated positioning system, as recited in claim 31, wherein after computation of said position and velocity, said position and velocity errors calculated by said Kalman filter are used in said attitude position velocity computation module to correct said inertial solution.

33. An enhanced integrated positioning system, as recited in claim 32, wherein said attitude errors computed by said Kalman filter is sent to said attitude position velocity computation module to perform attitude correction in said attitude position velocity computation module.

34. An enhanced integrated positioning system, as recited in claim 32, wherein said attitude errors computed by said Kalman filter is sent to said transformation matrix computation module to perform said attitude correction before said attitude position velocity computation module.

35. An enhanced integrated positioning system, as recited in claim 32, 33 or 34, wherein the corrected inertial solution obtained from said attitude position velocity computation module is passed to said Kalman filter to construct said measurements of said Kalman filter, and that the corrected velocity and accelerate is passed to microprocessor of said GPS processor to aid said global positioning system satellite signal carrier phase and code tracking, wherein attitude, position, and velocity computed by said attitude position velocity computation module are sent to said earth and vehicle rate computation module to calculate an Earth rotation rate and a vehicle rotation rate which are sent to said transformation matrix computation module, wherein said attitude, position, and velocity information is send to said I/O interface which provides a navigation data source for avionics systems onboard a vehicle.

36. An enhanced integrated positioning system, as recited in claim 35 wherein said Kalman filter is a robust Kalman filter for providing near-optimal performance over a large class of process and measurement models and for blending GPS measurements and said inertial sensor measurements.

37. An enhanced integrated positioning system, as recited in claim 36, wherein said robust Kalman filter comprises a GPS error compensation module for gathering said pseudorange and Doppler frequency of said GPS measurements from said GPS processor, and said position and velocity corrections from an updating state vector module to perform GPS error compensation to form corrected GPS raw data, including pseudorange, and Doppler frequency, which are sent to a preprocessing module, wherein said preprocessing module receives GPS satellite ephemeris from said GPS processor said corrected GPS raw data from said GPS error compensation module, said vehicle altitude measurement from said altitude measurement device, and INS solutions from said INS processor, said preprocessing module performing calculation of state transit matrix and sending with said state vector to a state vector prediction module, wherein said calculated state transit matrix is also sent to a covariance propagation module which calculates a measurement matrix and a current measurement vector according to a computed measurement matrix and a measurement model, and that said measurement matrix and said computed current measurement vector are passed to a computing measurement residue module, said state vector prediction module receiving said state transit matrix and said state vector from said preprocessing module to perform state prediction of current epoch, said predicted current state vector being passed to said computing measurement residue module which receives predicted current state vector from said state vector prediction module and said measurement matrix and said current measurement vector from said preprocessing module, wherein said computing measurement residue module calculates measurement residues by subtracting said multiplication of said measurement matrix and said predicted current state vector from said current measurement vector, and said measurement residues are sent to a residue monitor module and said updating state vector module, wherein said residue monitor module performs a discrimination on said measurement residues received from said computing measurement residue module, wherein said covariance propagation module gathers covariance of system process from said residue monitor module, said state transit matrix from said preprocessing module, and covariance of estimated error to calculate current covariance of said estimated error which is sent to a computing optimal gain module, wherein said computing optimal gain module receives said current covariance of said estimated error from said covariance computing module to compute optimal gain which is passed to a covariance updating module and said updating state vector module, said covariance updating module updating said covariance of said estimated error and sending to said covariance propagation module, wherein said updating state vector module receives said optimal gain from said computing optimal gain module and said measurement residues from said computing measurement residue module, said updating state vector calculating said current estimate of state vector including position, velocity and attitude errors and sending to said GPS error compensation module and said INS processor.

38. An enhanced integrated positioning system, comprising:

a global positioning system (GPS) processor for providing location related information;

an inertial measurement unit (IMU) for providing inertial measurements including body angular rates and specific forces;

an altitude measurement generator for providing vehicle altitude measurement, wherein said altitude measurement generator is an altitude measurement device for providing an altitude measurement above mean sea level (MSL);

a central navigation processor, which is connected with said GPS processor, said IMU and said altitude measurement device, for fusing said location related information from said GPS processor, said inertial measurements from said IMU and said altitude measurement from said altitude measurement generator to produce navigation data of a platform, including position, velocity and attitude of said platform; and

an input/output (I/O) interface, which is connected to said central navigation processor, for outputting said navigation data;

wherein said GPS processor provides GPS location data;

wherein said central navigation processor connected with said GPS processor, said IMU and said altitude measurement device, said central navigation processor comprising an inertial navigation system (INS) processor and a Kalman filter;

wherein said GPS location data are passed to said central navigation processor, said altitude measurement above MSL is passed to said Kalman filter, and said inertial measurements are inject into said inertial navigation system (INS) processor;

wherein outputs of said INS processor, said altitude measurement above MSL and said GPS location data are blended in said Kalman filter, and that an output of said Kalman filter is fed back to said INS processor to correct an INS navigation solution outputting from said central navigation processor to said I/O interface;

wherein a GPS navigation processor of said GPS processor outputs said GPS location data, global positioning system satellite ephemeris, and atmosphere parameters to said Kalman filter.

wherein said INS processor processes said inertial measurements, which are body angular rates and specific forces, and said position error, velocity error, and attitude error coming from said Kalman filter to derive said corrected navigation solution.

wherein said altitude measurement device sends said altitude measurement above MSL to said Kalman filter.

39. An enhanced integrated positioning system, as recited in claim 38, wherein said INS processor comprises an IMU I/O interface, an IMU error compensation module, a coordinate transformation computation module, an attitude position velocity computation module, a transformation matrix computation module, and an earth and vehicle rate computation module, wherein said IMU I/O interface collects said signal of said body angular rates and specific forces from said IMU for processing and converting to digital data which are corrupted by said inertial sensor measurement errors to form contaminated data that are passed to said IMU error compensation module, wherein said IMU error compensation module receives sensor error estimates derived from said Kalman filter to perform IMU error mitigation on said IMU data, said corrected inertial data being sent to said coordinate transformation computation module and said transformation matrix computation module, where said body angular rates are sent to said transformation matrix computation module and said specific forces are sent said coordinate transformation computation module, wherein said transformation matrix computation module receives said body angular rates from said IMU error computation module and an earth and vehicle rate from said earth and vehicle rate computation module to perform transformation matrix computation, said transformation matrix computation module sending said transformation matrix to said coordinate transformation computation module and attitude position velocity computation module, an attitude update algorithm in said transformation matrix computation module using said quaternion method because of its advantageous numerical and stability characteristics, wherein said coordinate transformation module collects said specific forces from said IMU error computation module and said transformation matrix from said transformation matrix computation module to perform said coordinate transformation, said coordinate transformation computation sending said specific forces transferred into said coordinate system presented by said transformation matrix to said attitude position velocity computation module, wherein said attitude position velocity computation module receives said transformed specific forces from said coordinate transformation computation module and said transformation matrix from said transformation matrix computation module to perform said attitude, position, velocity update.

40. An enhanced integrated positioning system, as recited in claim 39, wherein after computation of said position and velocity, said position and velocity errors calculated by said Kalman filter are used in said attitude position velocity computation module to correct said inertial solution.

41. An enhanced integrated positioning system, as recited in claim 40, wherein said attitude errors computed by said Kalman filter is sent to said attitude position velocity computation module to perform attitude correction in said attitude position velocity computation module.

42. An enhanced integrated positioning system, as recited in claim 40, wherein said attitude errors computed by said Kalman filter is sent to said transformation matrix computation module to perform said attitude correction before said attitude position velocity computation module.

43. An enhanced integrated positioning system, as recited in claim 41 or 42, wherein the corrected inertial solution obtained from said attitude position velocity computation module is passed to said Kalman filter to construct said measurements of said Kalman filter, wherein attitude, position, and velocity computed by said attitude position velocity computation module are sent to said earth and vehicle rate computation module to calculate an Earth rotation rate and a vehicle rotation rate which are sent to said transformation matrix computation module, wherein said attitude, position, and velocity information is send to said I/O interface which provides a navigation data source for avionics systems onboard a vehicle.

44. An enhanced integrated positioning system, as recited in claim 43, wherein said Kalman filter is a robust Kalman filter for providing near-optimal performance over a large class of process and measurement models and for blending GPS location data, said altitude measurement above MSL and said inertial sensor measurements.

45. An enhanced integrated positioning system, as recited in claim 44, wherein said robust Kalman filter comprises a GPS error compensation module for gathering said GPS location data from said GPS processor, and said position and velocity corrections from an updating state vector module to perform GPS error compensation to form corrected GPS location data, which are sent to a preprocessing module, wherein said preprocessing module receives GPS satellite ephemeris from said GPS processor said corrected GPS location data from said GPS error compensation module, said altitude measurement above MSL from said altitude measurement device, and INS solutions from said INS processor, said preprocessing module performing calculation of state transit matrix and sending with said state vector to a state vector prediction module, wherein said calculated state transit matrix is also sent to a covariance propagation module which calculates a measurement matrix and a current measurement vector according to a computed measurement matrix and a measurement model, and that said measurement matrix and said computed current measurement vector are passed to a computing measurement residue module, said state vector prediction module receiving said state transit matrix and said state vector from said preprocessing module to perform state prediction of current epoch, said predicted current state vector being passed to said computing measurement residue module which receives predicted current state vector from said state vector prediction module and said measurement matrix and said current measurement vector from said preprocessing module, wherein said computing measurement residue module calculates measurement residues by subtracting said multiplication of said measurement matrix and said predicted current state vector from said current measurement vector, and said measurement residues are sent to a residue monitor module and said updating state vector module, wherein said residue monitor module performs a discrimination on said measurement residues received from said computing measurement residue module, wherein said covariance propagation module gathers covariance of system process from said residue monitor module, said state transit matrix from said preprocessing module, and covariance of estimated error to calculate current covariance of said estimated error which is sent to a computing optimal gain module, wherein said computing optimal gain module receives said current covariance of said estimated error from said covariance computing module to compute optimal gain which is passed to a covariance updating module and said updating state vector module, said covariance updating module updating said covariance of said estimated error and sending to said covariance propagation module, wherein said updating state vector module receives said optimal gain from said computing optimal gain module and said measurement residues from said computing measurement residue module, said updating state vector calculating said current estimate of state vector including position, velocity and attitude errors and sending to said GPS error compensation module and said INS processor.

46. An enhanced integrated positioning system, comprising:

a global positioning system (GPS) processor for providing location related information;

an inertial measurement unit (IMU) for providing inertial measurements including body angular rates and specific forces;

an altitude measurement generator for providing vehicle altitude measurement, wherein said altitude measurement generator is a radar altimeter for providing an altitude measurement above a terrain;

a central navigation processor, which is connected with said GPS processor, said IMU and said altitude measurement device, for fusing said location related information from said GPS processor, said inertial measurements from said IMU and said altitude measurement from said altitude measurement generator to produce navigation data of a platform, including position, velocity and attitude of said platform; and

an input/output (I/O) interface, which is connected to said central navigation processor, for outputting said navigation data;

wherein said GPS processor provides GPS location data;

wherein said central navigation processor connected with said GPS processor, said IMU and said radar altimeter, said central navigation processor comprising an inertial navigation system (INS) processor, a data fusion module, a terrain database, and a Kalman filter;

wherein said GPS location data are passed to said central navigation processor, output of said radar altimeter is passed to said data fusion module, and said inertial measurements are inject into said inertial navigation system (INS) processor;

wherein outputs of said INS processor, output of said data fusion module and said GPS location data are blended in said Kalman filter, and that an output of said Kalman filter is fed back to said INS processor to correct an INS navigation solution outputting from said central navigation processor to said I/O interface;

wherein a GPS navigation processor of said GPS processor outputs said GPS location data, global positioning system satellite ephemeris, and atmosphere parameters to said Kalman filter;

wherein said INS processor processes said inertial measurements, which are body angular rates and specific forces, and said position error, velocity error, and attitude error coming from said Kalman filter to derive said corrected navigation solution;

wherein said radar altimeter sends vehicle altitude measurement to said data fusion module, said INS processor sends said vehicle position information to said terrain database, said terrain database performs database query to derive a terrain height above the mean sea level and sends said terrain height to said data fusion module, said data fusion module receives said vehicle altitude measurement above terrain from said radar altimeter and said terrain height from said terrain database to derive a vehicle altitude above mean sea level, said vehicle altitude above mean sea level is sent to said Kalman filter.

47. An enhanced integrated positioning system, as recited in claim 46, wherein said INS processor comprises an IMU I/O interface, an IMU error compensation module, a coordinate transformation computation module, an attitude position velocity computation module, a transformation matrix computation module, and an earth and vehicle rate computation module, wherein said IMU I/O interface collects said signal of said body angular rates and specific forces from said IMU for processing and converting to digital data which are corrupted by said inertial sensor measurement errors to form contaminated data that are passed to said IMU error compensation module, wherein said IMU error compensation module receives sensor error estimates derived from said Kalman filter to perform IMU error mitigation on said IMU data, said corrected inertial data being sent to said coordinate transformation computation module and said transformation matrix computation module, where said body angular rates are sent to said transformation matrix computation module and said specific forces are sent said coordinate transformation computation module, wherein said transformation matrix computation module receives said body angular rates from said IMU error computation module and an earth and vehicle rate from said earth and vehicle rate computation module to perform transformation matrix computation, said transformation matrix computation module sending said transformation matrix to said coordinate transformation computation module and attitude position velocity computation module, an attitude update algorithm in said transformation matrix computation module using said quaternion method because of its advantageous numerical and stability characteristics, wherein said coordinate transformation module collects said specific forces from said IMU error computation module and said transformation matrix from said transformation matrix computation module to perform said coordinate transformation, said coordinate transformation computation sending said specific forces transferred into said coordinate system presented by said transformation matrix to said attitude position velocity computation module, wherein said attitude position velocity computation module receives said transformed specific forces from said coordinate transformation computation module and said transformation matrix from said transformation matrix computation module to perform said attitude, position, velocity update.

48. An enhanced integrated positioning system, as recited in claim 47, wherein after computation of said position and velocity, said position and velocity errors calculated by said Kalman filter are used in said attitude position velocity computation module to correct said inertial solution.

49. An enhanced integrated positioning system, as recited in claim 48, wherein said attitude errors computed by said Kalman filter is sent to said attitude position velocity computation module to perform attitude correction in said attitude position velocity computation module.

50. An enhanced integrated positioning system, as recited in claim 48, wherein said attitude errors computed by said Kalman filter is sent to said transformation matrix computation module to perform said attitude correction before said attitude position velocity computation module.

51. An enhanced integrated positioning system, as recited in claim 49 or 50, wherein the corrected inertial solution obtained from said attitude position velocity computation module is passed to said Kalman filter to construct said measurements of said Kalman filter, wherein attitude, position, and velocity computed by said attitude position velocity computation module are sent to said earth and vehicle rate computation module to calculate an Earth rotation rate and a vehicle rotation rate which are sent to said transformation matrix computation module, wherein said attitude, position, and velocity information is send to said I/O interface which provides a navigation data source for avionics systems onboard a vehicle.

52. An enhanced integrated positioning system, as recited in claim 50, wherein said Kalman filter is a robust Kalman filter for providing near-optimal performance over a large class of process and measurement models and for blending GPS location data, said altitude measurement above MSL and said inertial sensor measurements.

53. An enhanced integrated positioning system, as recited in claim 52, wherein said robust Kalman filter comprises a GPS error compensation module for gathering said GPS location data from said GPS processor, and said position and velocity corrections from an updating state vector module to perform GPS error compensation to form corrected GPS location data, which are sent to a preprocessing module, wherein said preprocessing module receives GPS satellite ephemeris from said GPS processor said corrected GPS location data from said GPS error compensation module, said altitude measurement above MSL from said altitude measurement device, and INS solutions from said INS processor, said preprocessing module performing calculation of state transit matrix and sending with said state vector to a state vector prediction module, wherein said calculated state transit matrix is also sent to a covariance propagation module which calculates a measurement matrix and a current measurement vector according to a computed measurement matrix and a measurement model, and that said measurement matrix and said computed current measurement vector are passed to a computing measurement residue module, said state vector prediction module receiving said state transit matrix and said state vector from said preprocessing module to perform state prediction of current epoch, said predicted current state vector being passed to said computing measurement residue module which receives predicted current state vector from said state vector prediction module and said measurement matrix and said current measurement vector from said preprocessing module, wherein said computing measurement residue module calculates measurement residues by subtracting said multiplication of said measurement matrix and said predicted current state vector from said current measurement vector, and said measurement residues are sent to a residue monitor module and said updating state vector module, wherein said residue monitor module performs a discrimination on said measurement residues received from said computing measurement residue module, wherein said covariance propagation module gathers covariance of system process from said residue monitor module, said state transit matrix from said preprocessing module, and covariance of estimated error to calculate current covariance of said estimated error which is sent to a computing optimal gain module, wherein said computing optimal gain module receives said current covariance of said estimated error from said covariance computing module to compute optimal gain which is passed to a covariance updating module and said updating state vector module, said covariance updating module updating said covariance of said estimated error and sending to said covariance propagation module, wherein said updating state vector module receives said optimal gain from said computing optimal gain module and said measurement residues from said computing measurement residue module, said updating state vector calculating said current estimate of state vector including position, velocity and attitude errors and sending to said GPS error compensation module and said INS processor.