Vehicle positioning method and system thereof

• US 6,167,347 A
• Filed: 02/08/1999
• Issued: 12/26/2000
• Est. Priority Date: 11/04/1998
• Status: Expired due to Term

• Current Assignee: American GNC Corporation
• Original Assignee: Ching-Fang Lin
• Inventors: Lin, Ching-Fang
• Primary Examiner(s): Cuchlinski, Jr., William A.
• Assistant Examiner(s): Beaulieu, Yonel
• Application Number:
  US09/246,883
• Time in Patent Office: 687 Days
• Field of Search: 701/200, 701/207, 701/213, 701/214, 701/215, 701/216, 701/220, 701/225, 701/300, 342/357.01, 342/357.02, 342/357.03, 342/357.04, 342/357.05, 342/357.06, 342/450, 342/451
• US Class Current: 701/214
• CPC Class Codes: G01C 21/165 combined with non-inertial navigation instruments
• CPC Class Codes: G01S 19/26 involving a sensor measurement for aiding acquisition or tracking
• CPC Class Codes: G01S 19/44 Carrier phase ambiguity resolution; Floating ambiguity; LAMBDA [Least-squares AMBiguity Decorrelation Adjustment] method

Abstract

An improved fully-coupled vehicle positioning process and system thereof can substantially solve the problems encountered in global positioning system-only and inertial navigation system-only, such as loss of global positioning satellite signal, sensibility to jamming and spoofing, and inertial solution'"'"'s drift over time, in which the velocity and acceleration from an inertial navigation processor are used to aid the code and carrier phase tracking of the global positioning system satellite signals, so as to enhance the performance of the global positioning and inertial integration system, even in heavy jamming and high dynamic environments. The improved fully-coupled GPS/IMU vehicle positioning system includes an IMU (inertial measurement unit) and a GPS processor which are connected to a central navigation processor to produce navigation solution that is output to an I/O (input/output) interface.

Claims

1. An improved vehicle positioning system, comprising:

a global positioning system (GPS) processor for providing GPS measurements including pseudorange, carrier phase, and Doppler shift;

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

a central navigation processor, which are connected with said GPS processor and said IMU, comprising an inertial navigation system (INS) processor, a Kalman filter, a and a carrier phase integer ambiguity resolution module; and

an input/output (I/O) interface connected to said central navigation processor;

wherein said GPS measurements are passed to said central navigation processor and said inertial measurements are injected into said inertial navigation system (INS) processor;

wherein an output of said INS processor and said GPS measurements are blended in said Kalman filter;

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 an output of said micro-processor of said GPS processor, an output of said INS processor and an output of 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 and said INS processor outputs navigation data to said I/O interface;

wherein said microprocessor of said GPS processor outputs pseudorange, 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 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 a quaternion method 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.

2. An improved vehicle positioning system, as recited in claim 1, 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.

3. An improved vehicle positioning system, as recited in claim 2, 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.

4. An improved vehicle positioning system, as recited in claim 2, 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.

5. An improved vehicle positioning system, as recited in claim 2, 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 are sent to said I/O interface which provides a navigation data source for avionics systems onboard a vehicle.

6. An improved vehicle positioning system, as recited in claim 3, 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 are sent to said I/O interface which provides a navigation data source for avionics systems onboard a vehicle.

7. An improved vehicle positioning system, as recited in claim 4, 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 are sent to said I/O interface which provides a navigation data source for avionics systems onboard a vehicle.

8. An improved vehicle positioning system, as recited in one of claims 1 to 7, 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, 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 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 a 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.

9. An improved vehicle positioning system, as recited in one of claims 1 to 7, 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.

10. An improved vehicle positioning system, as recited in claim 9, 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 global positioning system 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.

11. An improved vehicle positioning system, comprising:

a global positioning system (GPS) processor for providing GPS measurements including pseudorange, carrier phase, and Doppler shift;

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

a central navigation processor, which are connected with said GPS processor and said IMU, comprising an inertial navigation system (INS) processor, a robust Kalman filter, and a carrier phase integer ambiguity resolution module; and

an input/output (I/O) interface connected to said central navigation processor;

wherein said GPS measurements are passed to said central navigation processor and said inertial measurements are injected into said inertial navigation system (INS) processor;

wherein an output of said INS processor and said GPS measurements are blended in said robust Kalman filter;

an output of said robust Kalman filter is fed back to said INS processor to correct an INS navigation solution outputting from said central navigation processor to said 1/0 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 an output of said micro-processor of said GPS processor, an output of said INS processor and an output of said robust 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 robust Kalman filter to further improve positioning accuracy and said INS processor outputs navigation data to said I/O interface;

wherein said robust Kalman filter, which is adapted for providing near-optimal performance over a large class of process and measurement models and for blending GPS measurements and said inertial sensor measurements, 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, 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 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 a 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.

12. An improved vehicle positioning system, comprising:

a global positioning system (GPS) processor for providing GPS measurements including pseudorange, carrier phase, and Doppler shift;

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

a central navigation processor, which are connected with said GPS processor and said IMU, comprising an inertial navigation system (INS) processor, a robust Kalman filter, and a carrier phase integer ambiguity resolution module; and

an input/output (I/O) interface connected to said central navigation processor;

wherein said GPS measurements are passed to said central navigation processor and said inertial measurements are injected into said inertial navigation system (INS) processor;

wherein an output of said INS processor and said GPS measurements are blended in said robust Kalman filter;

an output of said robust 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 an output of said micro-processor of said GPS processor, an output of said INS processor and an output of said robust 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 robust Kalman filter to further improve positioning accuracy and said INS processor outputs navigation data to said I/O interface;

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

wherein said robust Kalman filter, which is adapted for providing near-optimal performance over a large class of process and measurement models and for blending GPS measurements and said inertial sensor measurements, 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, 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 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 a 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.

13. An improved vehicle positioning system, comprising:

a global positioning system (GPS) processor for providing GPS measurements including pseudorange, carrier phase, and Doppler shift;

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

a central navigation processor, which are connected with said GPS processor and said IMU, comprising an inertial navigation system (INS) processor, a robust Kalman filter, and a carrier phase integer ambiguity resolution module; and

an input/output (I/O) interface connected to said central navigation processor;

wherein said GPS measurements are passed to said central navigation processor and said inertial measurements are injected into said inertial navigation system (INS) processor;

wherein an output of said INS processor and said GPS measurements are blended in said robust Kalman filter;

an output of said robust 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 an output of said micro-processor of said GPS processor, an output of said INS processor and an output of said robust 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 robust Kalman filter to further improve positioning accuracy and said INS processor outputs navigation data to said I/O interface;

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

wherein said robust Kalman filter, which is adapted for providing near-optimal performance over a large class of process and measurement models and for blending GPS measurements and said inertial sensor measurements, 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, 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 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 a 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.

14. An improved vehicle positioning system, comprising:

a global positioning system (GPS) processor for providing GPS measurements including pseudorange, carrier phase, and Doppler shift;

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

a central navigation processor, which are connected with said GPS processor and said IMU, comprising an inertial navigation system (INS) processor, a Kalman filter, and a carrier phase integer ambiguity resolution module; and

an input/output (I/O) interface connected to said central navigation processor;

wherein said GPS measurements are passed to said central navigation processor and said inertial measurements are injected into said inertial navigation system (INS) processor;

wherein an output of said INS processor and said GPS measurements are blended in said Kalman filter;

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 an output of said micro-processor of said GPS processor, an output of said INS processor and an output of 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 and said INS processor outputs navigation data to said I/O interface;

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.

15. An improved vehicle positioning system, as recited in claim 14, 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 global positioning system 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.

17. An improved vehicle positioning system, as recited in claim 14, 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 global positioning system 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.

19. An improved vehicle positioning system, as recited in claim 14, 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 global positioning system 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.

16. An improved vehicle positioning system, comprising:

a global positioning system (GPS) processor for providing GPS measurements including pseudorange, carrier phase, and Doppler shift;

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

a central navigation processor, which are connected with said GPS processor and said IMU, comprising an inertial navigation system (INS) processor, a Kalman filter, and a carrier phase integer ambiguity resolution module; and

an input/output (I/O) interface connected to said central navigation processor;

wherein said GPS measurements are passed to said central navigation processor and said inertial measurements are injected into said inertial navigation system (INS) processor;

wherein an output of said INS processor and said GPS measurements are blended in said Kalman filter;

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 an output of said micro-processor of said GPS processor, an output of said INS processor and an output of 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 and said INS processor outputs navigation data to said I/O interface;

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

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.

18. An improved vehicle positioning system, comprising:

a global positioning system (GPS) processor for providing GPS measurements including pseudorange, carrier phase, and Doppler shift;

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

a central navigation processor, which are connected with said GPS processor and said IMU, comprising an inertial navigation system (INS) processor, a Kalman filter, and a carrier phase integer ambiguity resolution module; and

an input/output (I/O) interface connected to said central navigation processor;

wherein said GPS measurements are passed to said central navigation processor and said inertial measurements are injected into said inertial navigation system (INS) processor;

wherein an output of said INS processor and said GPS measurements are blended in said Kalman filter;

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 an output of said micro-processor of said GPS processor, an output of said INS processor and an output of 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 and said INS processor outputs navigation data to said I/O interface;

wherein said microprocessor of said GPS processor outputs pseudorange, 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 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.