Position correction method for vehicle navigation system

• US 5,374,933 A
• Filed: 01/05/1993
• Issued: 12/20/1994
• Est. Priority Date: 01/05/1993
• Status: Expired due to Term

• Current Assignee: TomTom International BV (TomTom NV)
• Original Assignee: Zexel Corporation
• Inventors: Kao, Wei-Wen
• Primary Examiner(s): Blum, Theodore M.
• Application Number:
  US08/000,950
• Time in Patent Office: 714 Days
• Field of Search: 342/357, 364/449
• US Class Current: 342/357.31
• CPC Class Codes: G01C 21/30 Map- or contour-matching
• CPC Class Codes: G01S 19/24 Acquisition or tracking or demodulation of signals transmitted by the system synchronisation aspects of direct sequence spread spectrum modulation H04B1/7073
• CPC Class Codes: G01S 19/26 involving a sensor measurement for aiding acquisition or tracking
• CPC Class Codes: G01S 19/40 Correcting position, velocity or attitude

Abstract

A vehicle navigation system is used to determine the absolute position of a vehicle with improved accuracy on freeways or rural highways. First, the system stores a known vehicle position in its memory. As the vehicle moves away from the known position, the system uses a variety of means to sense external signals. These means include satellite transmission receivers and magnetic compasses. When a change in the external signals occurs, the system recognizes the presence of a landmark which can then be used to set the vehicle'"'"'s position. To accomplish this, the system'"'"'s data processor searches a map data base, attempting to fix the position of the sensed landmark with respect to the initially stored known position. When the system identifies the most likely landmark, the position of the vehicle is then reset to that position.

Claims

1. A method for determining a current vehicle position in a vehicle navigation system having a map data base, the method comprising the steps of:

storing a first vehicle position;

moving the vehicle from the first vehicle position;

sensing an external signal while moving the vehicle;

detecting a change in the external signal caused by the presence of a landmark;

examining the map data base to find a most likely landmark position corresponding to the change in the external signal; and

updating the current vehicle position to the most likely landmark position.

2. A method as in claim 1 wherein the step of sensing an external signal comprises receiving a GPS signal transmitted from a satellite.

3. A method as in claim 2 wherein the step of detecting a change in the external signal comprises detecting a failure to receive the GPS signal.

4. A method as in claim 3 wherein the landmark comprises a structure under which the vehicle passes such that the GPS signal is temporarily blocked.

5. A method as in claim 4 wherein the structure is taken from the group consisting of overpasses, tunnels and bridges.

6. A method as in claim 1 wherein the step of sensing an external signal comprises sensing a geomagnetic field to provide a first heading signal.

7. A method as in claim 6 wherein the landmark comprises a structure causing anomalies in the geomagnetic field.

8. A method as in claim 7 wherein the structure is taken from the group consisting of bridges, tunnels, buildings and geologic formations.

9. A method as in claim 6 wherein the step of detecting a change in the external signal comprises comparing the first heading signal to a second heading signal, the second heading signal being independent of the geomagnetic field, to detect a difference between the first and second heading signals caused by the landmark.

10. A method as in claim 9 wherein the second heading signal is generated by a gyroscope.

11. A method as in claim 9 wherein the step of comparing comprises filtering out differences between the first and second heading signals not caused by the landmark.

12. A method as in claim 11 wherein the filter comprises a digital auto-regressive moving-average filter of the form:

##EQU3## where;

y(k) is a magnetic anomaly index;

k is a current sample time;

a_l are auto-regressive coefficients;

b_j are moving-average coefficients;

m is a number of past y(k) values included in a present value;

n is a number of present and past values of a filter input which are to be averaged; and

u(k) is the difference between the first heading signal and the second heading signal, u(k) being the input to the auto-regressive moving-average filter;

wherein the change in the geomagnetic signal is considered to be caused by the landmark when the magnetic anomaly index exceeds a predetermined value.

13. A method as in claim 1 further comprising:

measuring the distance between the first vehicle position and the current vehicle position to obtain a measured distance;

calculating an actual distance between the first vehicle position and the current vehicle position from the map data base; and

determining a distance calibration factor relating the measured distance to the actual distance.

14. Apparatus for determining a current vehicle position in a vehicle navigation system having a map data base, the apparatus comprising:

a memory for storing a first vehicle position;

a sensor for sensing an external signal while the vehicle moves; and

processing means coupled to the map data base, the memory and the sensor, the processing means comprising;

means for detecting a change in the external signal caused by the presence of a landmark;

means for examining the map data base to find a most likely landmark position corresponding to the change in the external signal; and

means for updating the current vehicle position to the most likely landmark position.

15. The apparatus of claim 14 wherein the external signal comprises a GPS signal transmitted from a satellite, and the sensor comprises a GPS receiver.

16. The apparatus of claim 15 wherein the means for detecting a change in the external signal detects a failure to receive the GPS signal.

17. The apparatus of claim 16 wherein the landmark comprises a structure under which the vehicle passes such that the GPS signal is temporarily blocked.

18. The apparatus of claim 17 wherein the structure is taken from the group consisting of overpasses, tunnels and bridges.

19. The apparatus of claim 14 wherein the sensor comprises a geomagnetic field sensor, the geomagnetic field sensor sensing a geomagnetic field and producing a first heading signal.

20. The apparatus of claim 19 wherein the landmark comprises a structure causing anomalies in the geomagnetic field.

21. The apparatus of claim 20 wherein the structure is taken from the group consisting of bridges, tunnels, buildings and geologic formations.

22. The apparatus of claim 19 wherein the means for detecting a change in the external signal comprises means for comparing the first heading signal to a second heading signal, the second heading signal being independent of the geomagnetic field, to detect a difference between the first heading signal and the second heading signal caused by the landmark.

23. The apparatus of claim 22 wherein the second heading signal is generated by a gyroscope.

24. The apparatus of claim 22 wherein the means for comparing comprises a filter for filtering out differences between the first and second heading signals not caused by the landmark.

25. The apparatus of claim 24 wherein the filter comprises a digital auto-regressive moving-average filter of the form:

##EQU4## where;

y(k) is a magnetic anomaly index;

k is a current sample time;

a_l are auto-regressive coefficients;

b_j are moving-average coefficients;

m is a number of past y(k) values included in a present value;

n is a number of present and past values of a filter input which are to be averaged; and

u(k) is the difference between the first heading signal and the second heading signal, u(k) being the input to the auto-regressive moving-average filter;

wherein the change in the geomagnetic signal is considered to be caused by the landmark when the magnetic anomaly index exceeds a predetermined value.

26. The apparatus of claim 14 further comprising a distance sensor for measuring the distance between the first vehicle position and the current vehicle position to obtain a measured distance, wherein the processor means comprises means for calculating an actual distance between the first vehicle position and the current vehicle position from the map data base, and means for determining a distance calibration factor relating the measured distance to the actual distance.