Full fusion positioning method for vehicle

• US 6,240,367 B1
• Filed: 02/22/1999
• Issued: 05/29/2001
• Est. Priority Date: 11/27/1998
• Status: Expired due to Term

• Current Assignee: American GNC Corporation
• Original Assignee: American GNC Corporation
• Inventors: Lin, Ching-Fang
• Primary Examiner(s): Chin, Gary
• Application Number:
  US09/256,509
• Time in Patent Office: 827 Days
• Field of Search: 701/207, 701/213, 701/214, 701/215, 701/216, 701/217, 701/220, 342/357.01, 342/357.06, 342/357.12, 342/357.14
• US Class Current: 701/214
• CPC Class Codes: G01C 21/28 with correlation of data from several navigational instruments
• CPC Class Codes: G01S 19/26 involving a sensor measurement for aiding acquisition or tracking
• CPC Class Codes: G01S 19/47 the supplementary measurement being an inertial measurement, e.g. tightly coupled inertial

Abstract

A full fusion positioning method, which can be implemented in the existing hardware, but is more amenable to the emerging wafer-scale integration hardware, comprises the steps of injecting a global positioning system signal received by a global positioning system antenna and a predicted pseudorange and delta range from a data fusion, and converting and tracking said global positioning system signal to obtain pseudorange and delta range measurement and errors of said pseudorange and delta range measurement, which are passed to said data fusion; receiving a vehicle angular rate and an acceleration signal/data from an inertial measurement unit and solving inertial navigation equations for obtaining a referencing navigation solution, including position, velocity, and attitude, which are passed to a data fusion; and fusing said pseudorange and delta range measurement and said errors of said pseudorange and delta range measurement of said global positioning system and said referencing navigation solution to obtain predicted pseudorange and delta range, optimal estimates of said referencing navigation solution errors and inertial sensor errors, and optimal position information.

Claims

1. A full fusion positioning method, comprising the steps of:

(a) receiving Global Positioning System (GPS) signals by a GPS receiver, which are Radio Frequency (RF) signals, within a current epoch for a carrier by a GPS antenna carried by said carrier and previous predicted pseudorange and delta range measurements for a previous epoch from a data fusion device carried by said carrier, and converting and tracking said GPS signals by using said GPS signals and said previous predicted pseudorange and delta range measurements to obtain a pseudorange and delta range measurements and tracking errors of said pseudorange and delta range measurements, which are passed to said data fusion device;

(b) producing an angular rate and an acceleration data for said carrier by an Inertial Measurement Unit (IMU) carried by said carrier within said current epoch, receiving optimal estimate of navigation solution errors and IMU errors for said previous epoch from said data fusion device, and solving inertial navigation equations by using said angular rate and said acceleration data to obtain a referencing navigation solution of said carrier, including position, velocity and attitude of said carrier, for said current epoch, which are passed to said data fusion device; and

(c) fusing said pseudorange measurement and delta range measurements, said tracking errors of said pseudorange and delta range measurements, and said referencing navigation solution for said current epoch, so as to;

produce current predicted pseudorange and delta range measurements for said current epoch;

produce optimal estimate of said referencing navigation solution errors and IMU errors for said current epoch and optimal estimate of clock offset and offset rate of said GPS receiver for said current epoch;

remove said errors of said referencing navigation solution using said optimal estimate of said referencing navigation solution errors and IMU errors to provide a corrected navigation solution; and

output said corrected navigation solution of said carrier.

2. A full fusion positioning method, as recited in claim 1, before the step (a), further comprising an initialization step of:

providing an initial predicted pseudorange and delta range measurements for an initial epoch wherein said initial predicted pseudorange and delta range measurements becomes said previous predicted pseudorange and delta range measurements during said current epoch in the step (a).

3. A full fusion positioning method, as recited in claim 2, wherein said initialization step is a conventional standard GPS signal acquisition step of providing initial GPS position and velocity data, wherein an initial GPS position and velocity data is used to compute said initial predicted pseudorange and delta range measurements.

4. A full fusion positioning method, as recited in claim 1, further comprising the following steps, after the step (c), for another current epoch after said current epoch through the steps (a) to (c), wherein said current epoch in the steps (a) to (c) becomes a previous current epoch in the following steps:

(d) receiving Global Positioning System (GPS) signals, which are Radio Frequency (RF) signals, within said another current epoch for said carrier by said GPS antenna and said predicted pseudorange and delta range measurements for said previous current epoch from said data fusion device, and converting and tracking said GPS signals by using said GPS signals and said current predicted pseudorange and delta range measurements obtained in the step (c) to obtain current pseudorange and delta range measurements and current tacking errors of said pseudorange and delta range measurements, which are passed to said data fusion device;

(e) producing an angular rate and an acceleration data for said carrier by said Inertial Measurement Unit (IMU) within said another current epoch, receiving current optimal estimate of navigation solution errors and IMU errors for said another current epoch from said data fusion device, and solving current inertial navigation equations using said angular rate and said acceleration data to obtain current referencing navigation solution of said carrier, including position, velocity, and attitude of said carrier, for said another current epoch which are passed to said data fusion device;

(f) fusing said pseudorange measurement and said delta range measurement, said tracking errors of said pseudorange and delta range measurements, and said current referencing navigation solution for said another current epoch, so as to;

produce another current predicted pseudorange and delta range measurements for said current epoch;

produce current optimal estimate of said current referencing navigation solution errors and IMU errors for said another current error and current optimal estimate of clock offset and offset rate of said GPS receiver for said another current epoch;

remove said current errors of said current referencing navigation solution using said current optimal estimate of said current referencing navigation solution errors and IMU errors to provide another corrected navigation solution; and

output said another corrected navigation solution of said carrier;

(g) repeating the steps (d) to (f) for each next current epoch.

5. A full fusion positioning method, as recited in claim 2, further comprising the following steps, after the step (c), for another current epoch after said current epoch through the steps (a) to (c), wherein said current epoch in the steps (a) to (c) becomes a previous current epoch in the following steps:

(d) receiving Global Positioning System (GPS) signals, which are Radio Frequency (RF) signals, within said another current epoch for said carrier by said GPS antenna and said predicted pseudorange and delta range measurements for said previous current epoch from said data fusion device, and converting and tracking said GPS signals by using said GPS signals and said current predicted pseudorange and delta range measurements obtained in the step (c) to obtain current pseudorange and delta range measurements and current tacking errors of said pseudorange and delta range measurements, which are passed to said data fusion device;

(e) producing an angular rate and an acceleration data for said carrier by said Inertial Measurement Unit (IMU) within said another current epoch, receiving current optimal estimate of navigation solution errors and IMU errors for said another current epoch from said data fusion device, and solving current inertial navigation equations using said angular rate and said acceleration data to obtain current referencing navigation solution of said carrier, including position, velocity, and attitude of said carrier, for said another current epoch which are passed to said data fusion device;

(f) fusing said pseudorange measurement and said delta range measurement, said tracking errors of said pseudorange and delta range measurements, and said current referencing navigation solution for said another current epoch, so as to;

produce another current predicted pseudorange and delta range measurements for said current epoch;

produce current optimal estimate of said current referencing navigation solution errors and IMU errors for said another current error and current optimal estimate of clock offset and offset rate of said GPS receiver for said another current epoch;

remove said current errors of said current referencing navigation solution using said current optimal estimate of said current referencing navigation solution errors and IMU errors to provide another corrected navigation solution; and

output said another corrected navigation solution of said carrier;

(g) repeating the steps (d) to (f) for each next current epoch.

6. A full fusion positioning method, as recited in claim 3, further comprising the following steps, after the step (c), for anther current epoch after said current epoch through the steps (a) to (c), wherein said current epoch in the steps (a) to (c) becomes a previous current epoch in the following steps:

(d) receiving Global Positioning System (GPS) signals, which are Radio Frequency (RF) signals, within said another current epoch for said carrier by said GPS antenna and said predicted pseudorange and delta range measurements for said previous current epoch from said data fusion device, and converting and tracking said GPS signals by using said GPS signals and said current predicted pseudorange and delta range measurements obtained in the step (c) to obtain current pseudorange and delta range measurements and current tacking errors of said pseudorange and delta range measurements, which are passed to said data fusion device;

(e) producing an angular rate and an acceleration data for said carrier by said Inertial Measurement Unit (IMU) within said another current epoch, receiving current optimal estimate of navigation solution errors and IMU errors for said another current epoch from said data fusion device, and solving current inertial navigation equations using said angular rate and said acceleration data to obtain current referencing navigation solution of said carrier, including position, velocity, and attitude of said carrier, for said another current epoch which are passed to said data fusion device;

(f) fusing said pseudorange measurement and said delta range measurement, said tracking errors of said pseudorange and delta range measurements, and said current referencing navigation solution for said another current epoch, so as to;

produce another current predicted pseudorange and delta range measurements for said current epoch;

produce current optimal estimate of said current referencing navigation solution errors and IMU errors for said another current error and current optimal estimate of clock offset and offset rate of said GPS receiver for said another current epoch;

remove said current errors of said current referencing navigation solution using said current optimal estimate of said current referencing navigation solution errors and IMU errors to provide another corrected navigation solution; and

output said another corrected navigation solution of said carrier;

(g) repeating the steps (d) to (f) for each next current epoch.

7. A full fusion positioning method, as recited in claim 1, 4, 5 or 6, wherein the step (a) further comprises the steps of:

(a-1) inputting said GPS signals received by said GPS antenna, which are radio frequency (RF) signals, to a RF/IF converter;

mixing said input GPS signals with first local signals from a local numerically controlled oscillator to form a first mixed GPS signals;

band-pass filtering said first mixed GPS signals into Intermediate Frequency (IF) GPS signals; and

sending said IF GPS signals to a IF/baseband converter;

(a-2) mixing said IF GPS signals from said RF/IF converter, which are received by said IF/baseband converter with second local signals from said local numerically controlled oscillator to form a second mixed GPS signals, wherein said second mixed GPS signals are amplified, low-pass filtered, and transformed onto baseband GPS signals which are sent to a A/D converter;

(a-3) receiving said baseband GPS signals from said IF/baseband converter, which are analog signals, by said A/D converter;

sampling said analog baseband GPS signals to form digital baseband GPS signals, and outputting said digital baseband GPS signals to a digital signal processing device;

(a-4) receiving said digital baseband GPS signals from said AD converter and said predicted pseudorange and delta range measurements from said data fusion device by said digital signal processing;

transforming said predicted pseudorange and delta range measurements to code delay and carrier Doppler shift data, respectively; and

deducing a pseudorange and delta range measurements, and tracking errors of said pseudorange and delta range for each tracked satellite, which are input to said data fusion device.

8. A full fusion positioning method, as recited in claim 7, wherein the step (a-4) further comprises the steps of:

receiving said digital baseband GPS signals from said (A/D) converter by a mixer, mixing said digital baseband GPS signals with local in-phase (I) and quadraphase (Q) signals from a sine-cosine generator, to form mixed local in-phase (I) and quadraphase (Q) data to a correlation module;

receiving said mixed local in-phase (I) and quadraphase (Q) data from said mixer and local codes generated from a code generator by said correlation module, which are used to perform a correlation computation, wherein results of said correlation computation are output to a maximum-Likelihood Estimator;

collecting N samples of said results of said correlation computation by said Maximum Likelihood Estimation, wherein maximum likelihood estimates of tracking errors of said code delay and carrier phase Doppler shift data are made by said Maximum Likelihood Estimation, and are transformed to said tracking errors of said pseudorange and delta range respectively, which are sent to said data fusion device;

accepting a predicted carrier Doppler shift by a code oscillator to compute a code rate, wherein a generated code with said code rate is formed by said code oscillator to a code generator;

accepting said generated code with said code rate from said code oscillator and a predicted code delay by said code generator, so as to generate a local prompt code, which is sent to said correlation module to compute pseudorange measurements, wherein said pseudorange measurements are output to said data fusion device and to perform demodulation of satellite ephemeris to obtain satellite ephemeris, which are output to said data fusion device; and

receiving said predicted carrier Doppler shift by a sine-cosine generator to generate said local in-phase (I) and quadraphase (Q) signals, which are sent to said mixer, and to compute said delta range measurements, which are sent to said data fusion device.

9. A full fusion positioning method, as recited in claim 1, 4, 5, or 6, wherein the step (b) further comprises the steps of:

(b-1) inputting said angular rate and acceleration data from said inertial measurement unit with three orthogonally mounted gyros and three orthogonally mounted accelerometers and said optimal estimate of IMU errors from said data fusion device to an error compensation module;

(b-2) compensating errors of said three axis angular rates and accelerations with said optimal estimate of IMU errors to form compensated three axis angular rates and compensated three axis accelerations, wherein said compensated three axis angular rates are output to an attitude matrix computation module and said three axis angular accelerations are output to a coordinate transformation module;

(b-3) receiving, by said attitude matrix computation module, said compensated three axis angular rates from said error compensation module, a rotation rate vector of a local navigation frame (n frame) relative to an inertial frame (i frame) from an earth and vehicle rate computation module, and said optimal estimate of referencing navigation solution errors from said data fusion device, which are used to perform an update of an attitude matrix from a body frame (b frame) to said navigation frame (n frame) and to remove error of said attitude matrix, wherein said updated attitude matrix is output to said coordinate transformation module and a referencing navigation computation module,

(b-4) accepting, by said coordinate transformation module, said compensated accelerations from said error compensation module, which are expressed in the body frame, and said attitude matrix from said attitude matrix computation module, which used to transform said accelerations expressed in said body frame to accelerations expressed in said navigation frame, wherein said accelerations expressed in said navigation frame are output to said referencing navigation computation module;

(b-5) receiving, by said referencing navigation computation module, said accelerations expressed in said navigation frame from said coordinate transformation, and said attitude matrix obtained from said attitude matrix computation, and said optimal estimate of the referencing navigation errors from said data fusion device, which are used to compute said referencing position, velocity, and attitude, and to remove errors of said position and velocity solution, wherein said referencing navigation solution, including said position, velocity, and attitude are output to said earth and vehicle rate computation module and said data fusion device; and

(b-6) receiving, by said Earth and vehicle rate computation module, said referencing navigation solution from said referencing navigation module, which is used to compute said rotation rate vector of said local navigation frame (n frame) relative to said inertial frame (i frame), which is output to said attitude matrix computation module.

10. A full fusion positioning method, as recited in claim 7, wherein the step (b) further comprises the steps of:

(b-1) inputting said angular rate and acceleration data from said inertial measurement unit with three orthogonally mounted gyros and three orthogonally mounted accelerometers and said optimal estimate of IMU errors from said data fusion device to an error compensation module;

(b-2) compensating errors of said three axis angular rates and accelerations with said optimal estimate of IMU errors to form compensated three axis angular rates and compensated three axis accelerations, wherein said compensated three axis angular rates are output to an attitude matrix computation module and said three axis angular accelerations are output to a coordinate transformation module;

(b-3) receiving, by said attitude matrix computation module, said compensated three axis angular rates from said error compensation module, a rotation rate vector of a local navigation frame (n frame) relative to an inertial frame (i frame) from an earth and vehicle rate computation module, and said optimal estimate of referencing navigation solution errors from said data fusion device, which are used to perform an update of an attitude matrix from a body frame (b frame) to said navigation frame (n frame) and to remove error of said attitude matrix, wherein said updated attitude matrix is output to said coordinate transformation module and a referencing navigation computation module,

(b-4) accepting, by said coordinate transformation module, said compensated accelerations from said error, compensation module, which are expressed in the body frame, and said attitude matrix from said attitude matrix computation module, which used to transform said accelerations expressed in said body frame to accelerations expressed in said navigation frame, wherein said accelerations expressed in said navigation frame are output to said referencing navigation computation module;

(b-5) receiving, by said referencing navigation computation module, said accelerations expressed in said navigation frame from said coordinate transformation, and said attitude matrix obtained from said attitude matrix computation, and said optimal estimate of the referencing navigation errors from said data fusion device, which are used to compute said referencing position, velocity, and attitude, and to remove errors of said position and velocity solution, wherein said referencing navigation solution, including said position, velocity, and attitude are output to said earth and vehicle rate computation module and said data fusion device; and

(b-6) receiving, by said Earth and vehicle rate computation module, said referencing navigation solution from said referencing navigation module, which is used to compute said rotation rate vector of said local navigation frame (n frame) relative to said inertial frame (i frame), which is output to said attitude matrix computation module.

11. A full fusion positioning method, as recited in claim 8, wherein the step (b) further comprises the steps of:

(b-1) inputting said angular rate and acceleration data from said inertial measurement unit with three orthogonally mounted gyros and three orthogonally mounted accelerometers and said optimal estimate of IMU errors from said data fusion device to an error compensation module;

(b-2) compensating errors of said three axis angular rates and accelerations with said optimal estimate of IMU errors to form compensated three axis angular rates and compensated three axis accelerations, wherein said compensated three axis angular rates are output to an attitude matrix computation module and said three axis angular accelerations are output to a coordinate transformation module;

(b-3) receiving, by said attitude matrix computation module, said compensated three axis angular rates from said error compensation module, a rotation rate vector of a local navigation frame (n frame) relative to an inertial frame (i frame) from an earth and vehicle rate computation module, and said optimal estimate of referencing navigation solution errors from said data fusion device, which are used to perform an update of an attitude matrix from a body frame (b frame) to said navigation frame (n frame) and to remove error of said attitude matrix, wherein said updated attitude matrix is output to said coordinate transformation module and a referencing navigation computation module,

(b-4) accepting, by said coordinate transformation module, said compensated accelerations from said error compensation module, which are expressed in the body frame, and said attitude matrix from said attitude matrix computation module, which used to transform said accelerations expressed in said body frame to accelerations expressed in said navigation frame, wherein said accelerations expressed in said navigation frame are output to said referencing navigation computation module;

(b-5) receiving, by said referencing navigation computation module, said accelerations expressed in said navigation frame from said coordinate transformation, and said attitude matrix obtained from said attitude matrix computation, and said optimal estimate of the referencing navigation errors from said data fusion device, which are used to compute said referencing position, velocity, and attitude, and to remove errors of said position and velocity solution, wherein said referencing navigation solution, including said position, velocity, and attitude are output to said earth and vehicle rate computation module and said data fusion device; and

(b-6) receiving, by said Earth and vehicle rate computation module, said referencing navigation solution from said referencing navigation module, which is used to compute said rotation rate vector of said local navigation frame (n frame) relative to said inertial frame (i frame), which is output to said attitude matrix computation module.

12. A full fusion positioning method, as recited in claim 9, wherein the step (b-1) further comprises the steps of:

(b-1-1) receiving redundant angular rates and accelerations from said inertial measurement unit which comprises more than three skewed mounted gyros and more than three skewed mounted accelerometers;

(b-1-2) performing failure detection and isolation to detect and isolate potential gyro and accelerometer failures;

(b-1-3) solving said angular rate and acceleration data from said redundant angular rates and accelerations; and

(b-1-4) inputting said angular rate and acceleration data to an error compensation module.

13. A full fusion positioning method, as recited in claim 10, wherein the step (b-1) further comprises the steps of:

(b-1-1) receiving redundant angular rates and accelerations from said inertial measurement unit which comprises more than three skewed mounted gyros and more than three skewed mounted accelerometers;

(b-1-2) performing failure detection and isolation to detect and isolate potential gyro and accelerometer failures;

(b-1-3) solving said angular rate and acceleration data from said redundant angular rates and accelerations; and

(b-1-4) inputting said angular rate and acceleration data to an error compensation module.

14. A full fusion positioning method, as recited in claim 13, wherein the step (b-1) further comprises the steps of:

(b-1-1) receiving redundant angular rates and accelerations from said inertial measurement unit which comprises more than three skewed mounted gyros and more than three skewed mounted accelerometers;

(b-1-2) performing failure detection and isolation to detect and isolate potential gyro and accelerometer failures;

(b-1-3) solving said angular rate and acceleration data from said redundant angular rates and accelerations; and

(b-1-4) inputting said angular rate and acceleration data to an error compensation module.

15. A full fusion positioning method, as recited in claim 9, wherein the step (c) further comprises the steps of:

(c-1) passing said referencing navigation solution to a predicted pseudorange and delta range measurements computation module, so as to output as a full fusion positioning solution;

(c-2) accepting, by said predicted pseudorange and delta range measurements computation module, a satellite ephemeris from each digital signal processing of each tracked GPS satellite channel, said referencing navigation solution and said optimal estimate of said clock offset and offset rate of said GPS receiving set from said data fusion device;

(c-3) calculating said predicted pseudorange and delta range measurements for said each tracked GPS satellite channel using a GPS satellite position and velocity of said satellite ephemeris, a position and velocity of said referencing navigation solution, estimated clock offset and offset rate, a deterministic clock correction of said GSP signals, and computed atmospheric delays of said satellite ephemeris;

(c-4) outputting said predicted pseudorange and delta range measurements for said each tracked GPS satellite channel to a centralized filter and to said digital signal processing of said each tracked GPS satellite channel to enclose each signal tracking loop of said GPS signals;

(c-5) modeling, by said centralized filter, dynamics of referencing navigation parameter errors including three position parameter errors, three velocity parameter errors, three attitude parameter errors;

IMU errors including accelerometer measurement errors, gyro measurement errors, and said clock offset and offset rate of said GPS receiving set to form a system equation of said centralized filter, and

(c-6) processing measured pseudorange and delta range measurements and said tracking errors of said pseudorange and delta range measurements from said each digital signal processing for all said tracked GPS satellite channels, said predicted pseudorange and delta range measurements for all said tracked GPS satellite channels and satellite ephemeris, and said referencing navigation solution from said predicted pseudorange and delta range measurements computation module to form a measurement equation of said centralized filter and to perform the step of;

updating parameters of said system equation and said measurement equation;

computing parameters for a discrete model of said system equation;

computing parameters for a linear model of said measurement equation;

computing a time propagation of a state estimation and covariance matrix;

differencing said measured pseudorange and delta range measurements with said predicted pseudorange and delta range measurements to achieved differences which are compensated with said tracking errors of said pseudorange and delta range measurements and used as measurements of said centralized filter,

computing measurement residuals; and

updating said state estimation and covariance matrix and obtaining said optimal estimate of said referencing navigation solution errors, said IMU errors, and said clock offset and offset rate of said GPS receiving set.

16. A full fusion positioning method, as recited in claim 10, wherein the step (c) further comprises the steps of:

(c-1) passing said referencing navigation solution to a predicted pseudorange and delta range measurements computation module, so as to output as a full fusion positioning solution;

(c-2) accepting, by said predicted pseudorange and delta range measurements computation module, a satellite ephemeris from each digital signal processing of each tracked GPS satellite channel, said referencing navigation solution and said optimal estimate of said clock offset and offset rate of said GPS receiving set from said data fusion device;

(c-3) calculating said predicted pseudorange and delta range measurements for said each tracked GPS satellite channel using a GPS satellite position and velocity of said satellite ephemeris, a position and velocity of said referencing navigation solution, estimated clock offset and offset rate, a deterministic clock correction of said GSP signals, and computed atmospheric delays of said satellite ephemeris;

(c-4) outputting said predicted pseudorange and delta range measurements for said each tracked GPS satellite channel to a centralized filter and to said digital signal processing of said each tracked GPS satellite channel to enclose each signal tracking loop of said GPS signals;

(c-5) modeling, by said centralized filter, dynamics of referencing navigation parameter errors including three position parameter errors, three velocity parameter errors, three attitude parameter errors;

IMU errors including accelerometer measurement errors, gyro measurement errors, and said clock offset and offset rate of said GPS receiving set to form a system equation of said centralized filter; and

(c-6) processing measured pseudorange and delta range measurements and said tracking errors of said pseudorange and delta range measurements from said each digital signal processing for all said tracked GPS satellite channels, said predicted pseudorange and delta range measurements for all said tracked GPS satellite channels and satellite ephemeris, and said referencing navigation solution from said predicted pseudorange and delta range measurements computation module to form a measurement equation of said centralized filter and to perform the step of;

updating parameters of said system equation and said measurement equation;

computing parameters for a discrete model of said system equation;

computing parameters for a linear model of said measurement equation;

computing a time propagation of a state estimation and covariance matrix;

differencing said measured pseudorange and delta range measurements with said predicted pseudorange and delta range measurements to achieved differences which are compensated with said tracking errors of said pseudorange and delta range measurements and used as measurements of said centralized filter,

computing measurement residuals; and

updating said state estimation and covariance matrix and obtaining said optimal estimate of said referencing navigation solution errors, said IMU errors, and said clock offset and offset rate of said GPS receiving set.

17. A full fusion positioning method, as recited in claim 11, wherein the step (c) further comprises the steps of:

(c-1) passing said referencing navigation solution to a predicted pseudorange and delta range measurements computation module, so as to output as a full fusion positioning solution;

(c-2) accepting, by said predicted pseudorange and delta range measurements computation module, a satellite ephemeris from each digital signal processing of each tracked GPS satellite channel, said referencing navigation solution and said optimal estimate of said clock offset and offset rate of said GPS receiving set from said data fusion device;

(c-3) calculating said predicted pseudorange and delta range measurements for said each tracked GPS satellite channel using a GPS satellite position and velocity of said satellite ephemeris, a position and velocity of said referencing navigation solution, estimated clock offset and offset rate, a deterministic clock correction of said GSP signals, and computed atmospheric delays of said satellite ephemeris;

(c-4) outputting said predicted pseudorange and delta range measurements for said each tracked GPS satellite channel to a centralized filter and to said digital signal processing of said each tracked GPS satellite channel to enclose each signal tracking loop of said GPS signals;

(c-5) modeling, by said centralized filter, dynamics of referencing navigation parameter errors including three position parameter errors, three velocity parameter errors, three attitude parameter errors;

IMU errors including accelerometer measurement errors, gyro measurement errors, and said clock offset and offset rate of said GPS receiving set to form a system equation of said centralized filter; and

(c-6) processing measured pseudorange and delta range measurements and said tracking errors of said pseudorange and delta range measurements from said each digital signal processing for all said tracked GPS satellite channels, said predicted pseudorange and delta range measurements for all said tracked GPS satellite channels and satellite ephemeris, and said referencing navigation solution from said predicted pseudorange and delta range measurements computation module to form a measurement equation of said centralized filter and to perform the step of;

updating parameters of said system equation and said measurement equation;

computing parameters for a discrete model of said system equation;

computing parameters for a linear model of said measurement equation;

computing a time propagation of a state estimation and covariance matrix;

differencing said measured pseudorange and delta range measurements with said predicted pseudorange and delta range measurements to achieved differences which are compensated with said tracking errors of said pseudorange and delta range measurements and used as measurements of said centralized filter,

computing measurement residuals; and

updating said state estimation and covariance matrix and obtaining said optimal estimate of said referencing navigation solution errors, said IMU errors, and said clock offset and offset rate of said GPS receiving set.

18. A full fusion positioning method, as recited in claim 15, wherein after the step (c-6), further comprising an additional step of:

(c-7) inputting said measurement residuals from said centralized filter to a failure detection, isolation, and recovery (FDIR) module, so as to perform a test-statistical distribution of said input measurement residuals to detect and isolate a failure of said pseudorange and delta range measurements from the step (a) caused by a malfunction of said GPS receiver, wherein when said failure is detected, an indication of said malfunction of said GPS receiver is output by said FDIR to said centralized filter to isolate said malfunction or update said centralized filter.

19. A full fusion positioning method, as recited in claim 16, wherein after the step (c-6), further comprising an additional step of:

(c-7) inputting said measurement residuals from said centralized filter to a failure detection, isolation, and recovery (FDIR) module, so as to perform a test-statistical distribution of said input measurement residuals to detect and isolate a failure of said pseudorange and delta range measurements from the step (a) caused by a malfunction of said GPS receiver, wherein when said failure is detected, an indication of said malfunction of said GPS receiver is output by said FDIR to said centralized filter to isolate said malfunction or update said centralized filter.

20. A full fusion positioning method, as recited in claim 17, wherein after the step (c-6), further comprising an additional step of:

(c-7) inputting said measurement residuals from said centralized filter to a failure detection, isolation, and recovery (FDIR) module, so as to perform a test-statistical distribution of said input measurement residuals to detect and isolate a failure of said pseudorange and delta range measurements from the step (a) caused by a malfunction of said GPS receiver, wherein when said failure is detected, an indication of said malfunction of said GPS receiver is output by said FDIR to said centralized filter to isolate said malfunction or update said centralized filter.

21. A full fusion positioning method, as recited in claim 20, wherein the step (b-1) further comprises the steps of:

(b-1-1) receiving redundant angular rates and accelerations from said inertial measurement unit which comprises more than three skewed mounted gyros and more than three skewed mounted accelerometers;

(b-1-2) performing failure detection and isolation to detect and isolate potential gyro and accelerometer failures;

(b-1-3) solving said angular rate and acceleration data from said redundant angular rates and accelerations; and

(b-1-4) inputting said angular rate and acceleration data to an error compensation module.

22. A full fusion positioning method, as recited in claim 9, wherein the step (c) further comprises the steps of:

(c-1) passing said referencing navigation solution to a predicted pseudorange and delta range measurements computation module, so as to output as a full fusion positioning solution;

(c-2) accepting, by said predicted pseudorange and delta range measurements computation module, a satellite ephemeris from each digital signal processing of each tracked GPS satellite channel, said referencing navigation solution and said optimal estimate of said clock offset and offset rate of said GPS receiving set from said data fusion device;

(c-3) calculating said predicted pseudorange and delta range measurements for said each tracked GPS satellite channel using a GPS satellite position and velocity of said satellite ephemeris, a position and velocity of said referencing navigation solution, estimated clock offset and offset rate, a deterministic clock correction of said each tracked GPS satellite from said satellite ephemeris, and computed atmospheric delays of said GPS signals;

(c-4) outputting said predicted pseudorange and delta range measurements for said each tracked GPS satellite channel to each local filter for said each tracked GPS satellite channel and to said digital signal processing of said each tracked GPS satellite channel to enclose each signal tracking loop of said GPS signals;

(c-5) modeling, by said each local filter, dynamics of referencing navigation parameter errors including three position parameter errors, three velocity parameter errors, three attitude parameter errors;

IMU errors including accelerometer measurement errors, gyro measurement errors, and said clock offset and offset rate of said GPS receiving set to form a system equation of said each local filter;

(c-6) processing said measured pseudorange and delta range measurements and said tracking errors of said pseudorange and delta range measurements from said each digital signal processing for all said tracked GPS satellite channels, said predicted pseudorange and delta range measurements for all said tracked GPS satellite channels and satellite ephemeris, and said referencing navigation solution from said predicted pseudorange and delta range measurements computation module to form a measurement equation of said each local filter and to perform the step of;

updating parameters of said system equation and said measurement equation;

computing parameters for a discrete model of said system equation;

computing parameters for a linear model of said measurement equation;

computing a time propagation of a state estimation and covariance matrix;

differencing said measured pseudorange and delta range measurements with said predicted pseudorange and delta range measurements to achieved differences which are compensated with said tracking errors of said pseudorange and delta range measurements and used as measurements of said each local filter,

computing measurement residuals; and

updating said state estimation and covariance matrix and obtaining said optimal estimate of said referencing navigation solution errors, said IMU errors, and said clock offset and offset rate of said GPS receiving set; and

(c-7) inputting said state estimation and covariance matrix from said each local filter to a master filter for performing fusion processing to obtain global optimal state estimates.

23. A full fusion positioning method, as recited in claim 10, wherein the step (c) further comprises the steps of:

(c-1) passing said referencing navigation solution to a predicted pseudorange and delta range measurements computation module, so as to output as a full fusion positioning solution;

(c-2) accepting, by said predicted pseudorange and delta range measurements computation module, a satellite ephemeris from each digital signal processing of each tracked GPS satellite channel, said referencing navigation solution and said optimal estimate of said clock offset and offset rate of said GPS receiving set from said data fusion device;

(c-3) calculating said predicted pseudorange and delta range measurements for said each tracked GPS satellite channel using a GPS satellite position and velocity of said satellite ephemeris, a position and velocity of said referencing navigation solution, estimated clock offset and offset rate, a deterministic clock correction of said each tracked GPS satellite from said satellite ephemeris, and computed atmospheric delays of said GPS signals;

(c-4) outputting said predicted pseudorange and delta range measurements for said each tracked GPS satellite channel to a each local filter for said each tracked GPS satellite channel and to said digital signal processing of said each tracked GPS satellite channel to enclose each signal tracking loop of said GPS signals;

(c-5) modeling, by said each local filter, dynamics of referencing navigation parameter errors including three position parameter errors, three velocity parameter errors, three attitude parameter errors;

IMU errors including accelerometer measurement errors, gyro measurement errors, and said clock offset and offset rate of said GPS receiving set to form a system equation of said each local filter;

(c-6) processing said measured pseudorange and delta range measurements and said tracking errors of said pseudorange and delta range measurements from said each digital signal processing for all said tracked GPS satellite channels, said predicted pseudorange and delta range measurements for all said tracked GPS satellite channels and satellite ephemeris, and said referencing navigation solution from said predicted pseudorange and delta range measurements computation module to form a measurement equation of said each local filter and to perform the step of;

updating parameters of said system equation and said measurement equation;

computing parameters for a discrete model of said system equation;

computing parameters for a linear model of said measurement equation;

computing a time propagation of a state estimation and covariance matrix;

differencing said measured pseudorange and delta range measurements with said predicted pseudorange and delta range measurements to achieved differences which are compensated with said tracking errors of said pseudorange and delta range measurements and used as measurements of said each local filter,

computing measurement residuals; and

updating said state estimation and covariance matrix and obtaining said optimal estimate of said referencing navigation solution errors, said IMU errors, and said clock offset and offset rate of said GPS receiving set; and

(c-7) inputting said state estimation and covariance matrix from said each local filter to a master filter for performing fusion processing to obtain global optimal state estimates.

24. A full fusion positioning method, as recited in claim 11, wherein the step (c) further comprises the steps of:

(c-1) passing said referencing navigation solution to a predicted pseudorange and delta range measurements computation module, so as to output as a full fusion positioning solution;

(c-2) accepting, by said predicted pseudorange and delta range measurements computation module, a satellite ephemeris from each digital signal processing of each tracked GPS satellite channel, said referencing navigation solution and said optimal estimate of said clock offset and offset rate of said GPS receiving set from said data fusion device;

(c-3) calculating said predicted pseudorange and delta range measurements for said each tracked GPS satellite channel using a GPS satellite position and velocity of said satellite ephemeris, a position and velocity of said referencing navigation solution, estimated clock offset and offset rate, a deterministic clock correction of said each tracked GPS satellite from said satellite ephemeris, and computed atmospheric delays of said GPS signals;

(c-4) outputting said predicted pseudorange and delta range measurements for said each tracked GPS satellite channel to a each local filter for said each tracked GPS satellite channel and to said digital signal processing of said each tracked GPS satellite channel to enclose each signal tracking loop of said GPS signals;

(c-5) modeling, by said each local filter, dynamics of referencing navigation parameter errors including three position parameter errors, three velocity parameter errors, three attitude parameter errors;

IMU errors including accelerometer measurement errors, gyro measurement errors, and said clock offset and offset rate of said GPS receiving set to form a system equation of said each local filter;

(c-6) processing said measured pseudorange and delta range measurements and said tracking errors of said pseudorange and delta range measurements from said each digital signal processing for all said tracked GPS satellite channels, said predicted pseudorange and delta range measurements for all said tracked GPS satellite channels and satellite ephemeris, and said referencing navigation solution from said predicted pseudorange and delta range measurements computation module to form a measurement equation of said each local filter and to perform the step of;

updating parameters of said system equation and said measurement equation;

computing parameters for a discrete model of said system equation;

computing parameters for a linear model of said measurement equation;

computing a time propagation of a state estimation and covariance matrix;

differencing said measured pseudorange and delta range measurements with said predicted pseudorange and delta range measurements to achieved differences which are compensated with said tracking errors of said pseudorange and delta range measurements and used as measurements of said each local filter,

computing measurement residuals; and

updating said state estimation and covariance matrix and obtaining said optimal estimate of said referencing navigation solution errors, said IMU errors, and said clock offset and offset rate of said GPS receiving set; and

(c-7) inputting said state estimation and covariance matrix from said each local filter to a master filter for performing fusion processing to obtain global optimal state estimates.

25. A full fusion positioning method, as recited in claim 22, wherein after the step (c-7), further comprising an additional step of:

(c-8) inputting said measurement residuals from said centralized filter to a failure detection, isolation, and recovery (FDIR) module, so as to perform a test-statistical distribution of said input measurement residuals to detect and isolate a failure of said pseudorange and delta range measurements from the step (a) caused by a malfunction of said GPS receiver, wherein when said failure is detected, an indication of said malfunction of said GPS receiver is output by said FDIR to said centralized filter to isolate said malfunction or update said centralized filter.

26. A full fusion positioning method, as recited in claim 23, wherein after the step (c-7), further comprising an additional step of:

(c-8) inputting said measurement residuals from said centralized filter to a failure detection, isolation, and recovery (FDIR) module, so as to perform a test-statistical distribution of said input measurement residuals to detect and isolate a failure of said pseudorange and delta range measurements from the step (a) caused by a malfunction of said GPS receiver, wherein when said failure is detected, an indication of said malfunction of said GPS receiver is output by said FDIR to said centralized filter to isolate said malfunction or update said centralized filter.

27. A full fusion positioning method, as recited in claim 24, wherein after the step (c-7), further comprising an additional step of:

(c-8) inputting said measurement residuals from said centralized filter to a failure detection, isolation, and recovery (FDIR) module, so as to perform a test-statistical distribution of said input measurement residuals to detect and isolate a failure of said pseudorange and delta range measurements from the step (a) caused by a malfunction of said GPS receiver, wherein when said failure is detected, an indication of said malfunction of said GPS receiver is output by said FDIR to said centralized filter to isolate said malfunction or update said centralized filter.

28. A full fusion positioning method, as recited in claim 27, wherein the step (b-1) further comprises the steps of:

(b-1-1) receiving redundant angular rates and accelerations from said inertial measurement unit which comprises more than three skewed mounted gyros and more than three skewed mounted accelerometers;

(b-1-2) performing failure detection and isolation to detect and isolate potential gyro and accelerometer failures;

(b-1-3) solving said angular rate and acceleration data from said redundant angular rates and accelerations; and

(b-1-4) inputting said angular rate and acceleration data to an error compensation module.

29. A full fusion positioning method, as recited in claim 26, wherein, after the step (c-8), further comprises an additional step of:

feeding said state estimation, which includes said optimal estimate of inertial navigation solution errors, said clock offset and offset rate of said GPS receiver, and said IMU errors, and said covariance matrix obtained from said master filter, back to each said local filter to reset said local filter, so as to perform information-sharing among said master filter and said each local filter.

30. A full fusion positioning method, as recited in claim 26, wherein, after the step (c-8), further comprises an additional step of:

feeding said state estimation, which includes said optimal estimate of inertial navigation solution errors, said clock offset and offset rate of said GPS receiver, and said IMU errors, and said covariance matrix obtained from said master filter, back to each said local filter to reset said local filter, so as to perform information-sharing among said master filter and said each local filter.

31. A full fusion positioning method, as recited in claim 27, wherein, after the step (c-8), further comprises an additional step of:

feeding said state estimation, which includes said optimal estimate of inertial navigation solution errors, said clock offset and offset rate of said GPS receiver, and said IMU errors, and said covariance matrix obtained from said master filter, back to each said local filter to reset said local filter, so as to perform information-sharing among said master filter and said each local filter.

32. A full fusion positioning method, as recited in claim 28, wherein, after the step (c-8), further comprises an additional step of:

feeding said state estimation, which includes said optimal estimate of inertial navigation solution errors said clock offset and offset rate of said GPS receiver, and said IMU errors, and said covariance matrix obtained from said master filter, back to each said local filter to reset said local filter, so as to perform information-sharing among said master filter and said each local filter.