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An aided inertial navigation system and method for navigating a mobile object having constraints comprising an inertial measurement unit, a processor, and an error correction device. The inertial measurement unit provides acceleration data and/or angular velocity data of the mobile object. The proce

An aided inertial navigation system and method for navigating a mobile object having constraints comprising an inertial measurement unit, a processor, and an error correction device. The inertial measurement unit provides acceleration data and/or angular velocity data of the mobile object. The processor is adapted to receive the acceleration data and/or angular velocity data, and to provide output data with position output indicative of position of the mobile object. The error correction device receives as input, state and dynamics information and auxiliary input data including map information associated with the path, speed data, wheel-angle data and discrete data. The error correction device provides as output, state corrections to the processor that enhance accuracy of the position output. The state corrections are used by the processor to estimate position of the mobile object based on the constraints to the mobile object and the map information associated with the path.

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1. An aided inertial navigation system (AINS) for navigating a mobile object, said AINS comprising:an inertial measurement unit that provides acceleration data and angular velocity data of said mobile object, said mobile object having constraints which constrain mobility of said mobile object to a p

1. An aided inertial navigation system (AINS) for navigating a mobile object, said AINS comprising:an inertial measurement unit that provides acceleration data and angular velocity data of said mobile object, said mobile object having constraints which constrain mobility of said mobile object to a path;a processor that receives said acceleration data and angular velocity data from said inertial measurement unit, and provides output data with a position output indicative of position of said mobile object; andan error correction device that receives as input, state and dynamics information of said mobile object, and provides as output, state corrections to said processor;wherein said error correction device is provided with zero-azimuth-change observations when said mobile object is stationary to freeze the azimuth when said mobile object is stationary and to suppress azimuth drift, and said processor enhances said position output based on said state corrections and said constraints to said mobile object to increase accuracy of said position output. 2. The AINS of claim 1, wherein said error correction device further receives auxiliary input data including at least one of positional input data, map information associated with said path, speed data, wheel-angle data, and discrete data. 3. The AINS of claim 2, wherein said state corrections provided to said processor are based on said auxiliary input data as well as said state and dynamics information. 4. The AINS of claim 1, wherein said inertial measurement unit includes at least one of an accelerometer that provides said acceleration data, and a gyroscope that provides said angular velocity data. 5. The AINS of claim 4, wherein said inertial measurement unit includes at least one accelerometer and at least one gyroscope. 6. The AINS of claim 1, wherein said processor is an inertial navigation and sensor compensation unit and said output data further includes a velocity output indicative of speed of said mobile object, and an attitude output indicative of orientation of said mobile object. 7. The AINS of claim 1, wherein said processor is an inertial navigation and sensor compensation unit, and said output data further includes an accuracy output indicative of accuracy of said position output. 8. An aided inertial navigation system (AINS) for navigating a mobile object, said AINS comprising:an inertial measurement unit adapted to provide acceleration data and angular velocity data of said mobile object, said mobile object having constraints which constrain mobility of said mobile object to a path;a processor adapted to receive said acceleration data and angular velocity data from said inertial measurement unit, and to provide output data with a position output indicative of position of said mobile object, said processor being an inertial navigation and sensor compensation unit, and said output data further including an accuracy output indicative of accuracy of said position output; andan error correction device adapted to receive as input, state and dynamics information of said mobile object, and provide as output, state corrections to said processor;wherein said processor enhances said position output based on said state corrections and said constraints to said mobile object to increase accuracy of said position output, and said accuracy output is expressed as a confidence interval for distance along said path. 9. The AINS of claim 1, wherein said error correction device is a Kalman filter. 10. The AINS of claim 9, wherein said Kalman filter further receives auxiliary input data including at least one of positional input data, map information associated with said path, speed data, wheel-angle data, and discrete data. 11. The AINS of claim 10, wherein said positional input data is provided by at least one of Global Positioning System, Differential GPS, ultrasonic positioning system, and radio-frequency positioning system. 12. The AINS of claim 10, wherein said speed data is pro vided by at least one of an odometer, wheel tachometer, and Doppler radar. 13. The AINS of claim 10, wherein said wheel angle data is provided by at least one of wheel angle sensor and truck angle sensor. 14. The AINS of claim 10, wherein said discrete data is provided by at least one of a transponder and a rail detector. 15. The AINS of claim 2, wherein said map information includes coordinates of a series of map points marking at least one map segment. 16. The AINS of claim 15, wherein said processor further calculate a maximum distance error between a segment of said path and said at least one map segment. 17. The AINS of claim 15, wherein said map information further includes along-path distances between said series of map points. 18. The AINS of claim 1, wherein said mobile object is an automobile, and said path is defined by a road. 19. The AINS of claim 1, wherein said vehicle is at least one of a railcar and a trolley, and said path is defined by a track. 20. The AINS of claim 1, wherein said mobile object is a m obile probe, and said path is defined by a pipe. 21. An aided inertial navigation system (AINS) for navigating a mobile object, said AINS comprising:an inertial measurement unit that provides acceleration data and angular velocity data of said mobile object, said mobile object having constraints which constrain mobility of said mobile object to a path;a processor that receives said acceleration data and angular velocity data from said inertial measurement unit, constrains a lateral velocity of said mobile object to zero, and provides a plurality of output data for navigating said mobile object, said plurality of output data including a position output indicative of position of said mobile object; andan error correction device that:receives as input, state and dynamics information of said mobile object and auxiliary input data including at least one of positional input data, map information associated with said path, speed data, wheel angle data and discrete data; andprovides as output, state corrections to said processor, said state corrections being determined based on said auxiliary input data;wherein said processor enhances accuracy of said position output indicative of position of said mobile object based on said state corrections and said constrained lateral velocity. 22. An aided inertial navigation system (AINS) for navigating a mobile object, said AINS comprising:an inertial measurement unit that provides acceleration data and angular velocity data of said mobile object;a processor that receives said acceleration data and angular velocity data from said inertial measurement unit, constrains a lateral velocity of said mobile object to zero, and provides output data having position output indicative of position of said mobile object; anda Kalman filter that receives as input, state and dynamics information of said mobile object, and provides as output, state corrections to said processor, said Kalman filter being provided with zero-azimuth-change observations when said mobile object is stationary to freeze the azimuth when said mobile object is stationary and to suppress azimuth drift;wherein said processor enhances said position output based on said state corrections and said constrained lateral velocity to increase accuracy of said position output. 23. A method for navigating a mobile object comprising the steps of:constraining mobility of said mobile object to a path;monitoring acceleration and angular velocity of said mobile object;providing acceleration data and angular velocity data;determining output data having at least position output indicative of position of said mobile object based on said acceleration data and angular velocity data;providing zero-azimuth-change observations when said mobile object is stationary to freeze the azimuth when said mobile object is stationary and to suppress azimuth drift; andenhancing accuracy of said position output indicative of position of said mobile object b ased on said constraints to mobility of said mobile object. 24. The method of claim 23, further including the step of providing map information associated with said path, wherein said step of enhancing accuracy of said position output is further based on said map information. 25. The method of claim 23, wherein said step of enhancing accuracy of said position output is further based on state and dynamics information of said mobile object, said state and dynamics information being derived from said acceleration data and angular velocity data. 26. The method of claim 23, further including the steps of determining velocity and attitude of said mobile object, and providing a velocity output indicative of speed of said mobile object and an attitude output indicative of orientation of said mobile object. 27. The method of claim 23, further including the step of determining accuracy of said position output, and wherein said output data further includes an accuracy output indicative of accuracy of said position output. 28. The method of claim 23, wherein said step of enhancing accuracy of said position output includes the step of generating state corrections using a Kalman filter based on at least one of positional input data, speed data, map information, wheel angle data, and discrete data. 29. The method of claim 28, further including the step of determining smoothly varying distance along path for use as said speed data. 30. The method of claim 28, wherein said map information includes coordinates of a series of map points marking at least one map segment, and along-path distances between said series of points. 31. The method of claim 30, further including the steps of determining where position of said mobile object coincides with a known map point and further enhancing accuracy of said position output based on said known map point. 32. A method for navigating a mobile object comprising the steps of:constraining mobility of said mobile object to a path;monitoring acceleration and angular velocity of said mobile objectproviding acceleration data and angular velocity datadetermining output data having at least a position output indicative of position of said mobile object based on said acceleration data and angular velocity data;enhancing accuracy of said position output indicative of position of said mobile object based on said constraints to mobility of said mobile object, said step of enhancing accuracy of said position output including the step of generating state corrections using a Kalman filter based on at least one of positional input data, speed data, map information, wheel angle data, and discrete data, wherein said map information includes coordinates of a series of map points marking at least one map segment, and along-path distances between said series of points; andmonitoring along path distance and comparing said along path distance to length of said at least one map segment to determine accuracy of said map information. 33. A method for navigating a mobile object comprising the steps of:constraining mobility of said mobile object to a path;monitoring acceleration and angular velocity of said mobile object;providing acceleration data and angular velocity data;determining output data having at least a position output indicative of position of said mobile object based on said acceleration data and angular velocity data;enhancing accuracy of said position output indicative of position of said mobile object based on said constraints to mobility of said mobile object, said step of enhancing accuracy of said position output including the step of generating state corrections using a Kalman filter based on at least one of positional input data, speed data, map information, wheel angle data, and discrete data, wherein said map information includes coordinates of a series of map points marking at least one map segment, and along-path distances between said series of points; andcalculating a maximum distance error between a segm ent of said path and said at least one map segment. 34. A method for navigating a mobile object comprising the steps of:constraining mobility of said mobile object to a path;providing map information associated with said path;monitoring acceleration and angular velocity of said mobile object;providing acceleration data and angular velocity data;constraining lateral velocity mobile object to zero;determining output data with position output indicative of position of said mobile object based on said acceleration data and angular velocity data for navigating said mobile object; andenhancing accuracy of said position output based on said constraints lateral velocity and said map information associated with said path. 35. A method for navigating a mobile object comprising the steps of:monitoring acceleration and angular velocity of said mobile object and providing acceleration data and angular velocity data;constraining lateral velocity of said mobile object to zero;determining output data with a position output indicative of position of said mobile object for navigating said mobile object based on said acceleration data and angular velocity data;providing a Kalman filter that receives as input, state and dynamics information of said mobile object, and provides state corrections as outputs;providing said Kalman filter with zero-azimuth-change observations when said mobile object is stationary to freeze the azimuth when said mobile object is stationary and to suppress azimuth drift; andenhancing accuracy of said position output indicative of position of said mobile object based on said state corrections and said constrained lateral velocity. 36. The method of claim 35, further including the step of determining whether said mobile object is stationary. 37. The method of claim 36, further including the steps of establishing an azimuth reference value by sampling and saving a current azimuth value. 38. The method of claim 37, further including the step of establishing an azimuth reference error in said Kalman filter error state which is same as said azimuth reference value. 39. A method for navigating a mobile object comprising the steps of:monitoring acceleration and angular velocity of said mobile object and providing acceleration data and annular velocity data;determining output data with a position output indicative of position of said mobile object for navigating said mobile object based on said acceleration data and angular velocity data;providing a Kalman filter adapted to receive as input, state and dynamics information of said mobile object, and providing state corrections as outputs;providing said Kalman filter with zero-azimuth-change observations when said mobile object is stationary to enhance accuracy of said position output indicative of position of said mobile object;determining whether said mobile object is stationary;establishing an azimuth reference value by sampling and saving a current azimuth value;establishing an azimuth reference error in said Kalman filter error state which is same as said azimuth reference value; andfurther including the step of adjusting an error state covariance matrix to accurately reflect said azimuth reference error.