Fault-tolerant system, apparatus and method

• US 20060074558A1
• Filed: 11/09/2005
• Published: 04/06/2006
• Est. Priority Date: 11/26/2003
• Status: Abandoned Application

• Current Assignee: Jason Lee Speyer, Walton Ross Williamson
• Original Assignee: Jason Lee Speyer, Walton Ross Williamson
• Inventors: Speyer, Jason Lee, Williamson, Walton Ross
• Application Number:
  US11/272,222
• Publication Number:
  US 20060074558A1
• Time in Patent Office: Days
• US Class Current: 701/213
• CPC Class Codes: G01C 21/165 combined with non-inertial navigation instruments
• CPC Class Codes: G01S 19/15 Aircraft landing systems
• CPC Class Codes: G01S 19/18 Military applications
• CPC Class Codes: G01S 19/20 Integrity monitoring, fault detection or fault isolation of space segment
• CPC Class Codes: G01S 19/23 Testing, monitoring, correcting or calibrating of receiver elements
• 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
• CPC Class Codes: G01S 19/47 the supplementary measurement being an inertial measurement, e.g. tightly coupled inertial
• CPC Class Codes: G01S 19/51 Relative positioning

Abstract

A method, apparatus and system are described having a minimum variance estimator of state estimates typically in navigation embodiments where a sensor and/or effecter fault detecting module is adapted to execute residual testing steps using the Multiple Hypothesis Wald Sequential Probability Ratio test, the Multiple Hypothesis Shiryayev Sequential Probability Ratio test, the Chi-Square test and combinations thereof to determine the likelihood of sensor and/or actuator fault occurrences and thereafter isolate the effects of the one or more identified fault from the state estimates.

Claims

1. A method for maintaining estimation integrity of a recursive stochastic filter comprising the steps of:

measuring the output of a measurement device

determining a fault-free residual from a residual process by operating on an updated recursive stochastic filter state estimation residual with a projection model;

determining a first probabilistic estimate of a fault from;

at least one projected recursive stochastic filter state estimation residual;

at least one measurement model, and at least one hypothesized first fault model, wherein the determining of a first probabilistic estimate of a fault is based on at least one of;

a Multiple Hypothesis Wald Sequential Probability Ratio Test; and

a Multiple Hypothesis Shiryayev Sequential Probability Ratio test;

testing for a fault based on the determined probabilistic estimate of a fault; and

outputting at least one probabilistic estimate of a fault

2. The method of claim 1 wherein the step of determining a first probabilistic estimate of fault comprises the steps of:

determining a preliminary probabilistic estimate of a fault based on a Wald Sequential Probability Ratio test; and

if the determined preliminary probabilistic estimate of fault is above a threshold, testing with a Multiple Hypothesis Shiryayav Sequential Probability Ratio.

3. The method of claim 2 further comprising the step of:

re-initializing one or more probabilistic estimates in the Multiple Hypothesis Shiryayav Sequential Probability Ratio Test, if the step of testing with the Multiple Hypothesis Shiryayav Sequential Probability Ratio returns a fault detection.

4. The method of claim 1 wherein the step of determining the first probabilistic estimate of a fault further includes determining the first probabilistic estimate of a fault from at least one second hypothesized fault model.

5. The method for maintaining estimation integrity of a recursive stochastic filter of claim 4 wherein method further comprises the step of generating a projector to annihilate at least one of the at least one second hypothesized fault model.

6. The method of claim 1 wherein the recursive stochastic filter includes a measurement noise covariance, the method further comprising the step of estimating one or more adjustments to the measurement noise covariance based on an output history of the residual.

7. The method of claim 1 wherein the recursive stochastic filter includes at least one measurement bias estimate, the method further comprising the step of estimating one or more adjustments to the at least one measurement bias based on an output history of the residual.

8. The method of claim 1 wherein a first portion of a system state of the recursive stochastic filter is unaffected by a fault direction derived for an output of the residual process and a second portion of a system state of the recursive stochastic filter is affected by the fault direction, the method further comprising the steps of:

constructing an annihilator for removing the unaffected portion of the system state of the recursive stochastic filter;

annihilating the unaffected portion of the system state of the recursive stochastic filter; and

estimating a fault signal time history based on the affected portion of the system state of the recursive stochastic filter.

9. The method of claim 1 wherein a first portion of a system state of the recursive stochastic filter is unaffected by a fault direction derived for an output of the residual process and a second portion of a system state of the recursive stochastic filter is affected by the fault direction, the method further comprising the steps of:

constructing an annihilator for removing the unaffected portion of the system state of the recursive stochastic filter;

annihilating the unaffected portion of the system state of the recursive stochastic filter; and

estimating a fault-free history based on the un-affected portion of the system state of the recursive stochastic filter.

10. The method of claim 1 further including a step of providing the fault free estimate to a control system adapted to execute at least one of the following steps:

generate a feedback command to a system, initiate fault repair, and modify one or more estimation steps.

11. The method of claim 1 wherein the step of determining a first probabilistic estimate of fault comprises the step of determining a preliminary probabilistic estimate of a fault based on a Chi-Square test.

12. An apparatus comprising:

at least one measurement device operabley coupled with an at least one processor adapted to receive an output of the measurement device;

the at least one processor further adapted to;

determine a fault-free residual from a residual process by operating on an updated recursive stochastic filter state estimation residual with a projection model;

determine a first probabilistic estimate of a fault from;

at least one projected recursive stochastic filter state estimation residual;

at least one measurement model; and

at least one hypothesized first fault model, wherein the determining of a first probabilistic estimate of a fault is based on at least one of;

a Multiple Hypothesis Wald Sequential Probability Ratio Test;

a Multiple Hypothesis Shiryayev Sequential Probability Ratio test; and

a Chi-Square Test;

test for a fault based on the determined probabilistic estimate of a fault; and

output at least one probabilistic estimate of a fault.

13. The apparatus of claim 12 wherein the at least one processor is further adapted, when determining the first probabilistic estimate of fault, to:

determine a preliminary probabilistic estimate of a fault based on a Wald Sequential Probability Ratio test; and

test with a Multiple Hypothesis Shiryayav Sequential Probability Ratio when the determined preliminary probabilistic estimate of fault is above a threshold,.

14. The apparatus of claim 12 wherein the at least one processor is further adapted to re-initialize one or more probabilistic estimates in the Multiple Hypothesis Shiryayav Sequential Probability Ratio Test when the Multiple Hypothesis Shiryayav Sequential Probability Ratio returns a fault detection.

15. The apparatus of claim 12 wherein the at least one processor is adapted to determine the first probabilistic estimate of a fault is further adapted to determine the first probabilistic estimate of a fault from at least one second hypothesized fault model.

16. The apparatus of claim 15 wherein the method further comprises the step of generating a projector to annihilate at least one of the at least one second hypothesized fault model.

17. The apparatus of claim 12 wherein the at least one processor is adapted to execute a recursive stochastic filter comprising a measurement noise covariance, the at least one processor further adapted to estimate one or more adjustments to the measurement noise covariance based on an output history of the residual.

18. The apparatus of claim 12 wherein the at least one processor is adapted to execute a recursive stochastic filter comprising at least one measurement bias estimate, the at least one processor being further adapted to estimate one or more adjustments to the at least one measurement bias based on an output history of the residual.

19. The apparatus of claim 12 wherein the at least one processor is adapted to execute a first portion of a system state of the recursive stochastic filter, the first portion of the system state being unaffected by a fault direction derived for an output of the residual process, and the at least one processor is adapted to execute a second portion of a system state of the recursive stochastic filter, the second portion being affected by the fault direction, the method further comprising the steps of:

constructing an annihilator for removing the unaffected portion of the system state of the recursive stochastic filter,

annihilating the unaffected portion of the system state of the recursive stochastic filter, and

estimating a fault signal time history based on the affected portion of the system state of the recursive stochastic filter.

20. The apparatus of claim 12 wherein the at least one processor is adapted to execute a first portion of a system state of the recursive stochastic filter, the first portion of the system state being unaffected by a fault direction derived for an output of the residual process, and the at least one processor is adapted to execute a second portion of a system state of the recursive stochastic filter, the second portion being affected by the fault direction, the at least one processor is further adapted to:

construct an annihilator for removing the unaffected portion of the system state of the recursive stochastic filter;

annihilate the unaffected portion of the system state of the recursive stochastic filter; and

estimate a fault-free history based on the un-affected portion of the system state of the recursive stochastic filter.

21. The apparatus of claim 12 wherein the at least one processor is further adapted to provide a fault free estimate to a control system adapted to execute at least one of the following steps:

generate a feedback command to a system, initiate fault repair, and modify one or more estimation steps.

22. The apparatus of claim 12 wherein the at least one processor is further adapted to determine a first probabilistic estimate of fault via a preliminary probabilistic estimate of a fault based on a Chi-Square test.

23. The apparatus of claim 12 wherein the measurement device is a global positioning satellite (GPS) receiver adapted to provide at least one measurement comprising at least one of:

time, position, velocity, pseudorange, pseudorange rate, and carrier phase;

wherein the at least one processor is further adapted to support a hypothesized fault model for at least one measurement and output at least one probabilistic estimate of a fault for the at least one GPS receiver measurement.

24. The apparatus of claim 12 wherein the measurement device is a global positioning satellite (GPS) receiver adapted to provide at least one measurement comprising at least one of:

position, velocity, pseudorange, pseudorange rate, and carrier phase;

wherein the at least one processor of claim 12 is further adapted to support a model of troposphere error.

25. The apparatus of claim 24 wherein the apparatus is further instrumented to take at least one of the following:

a temperature measurement proximate to the apparatus;

a static atmospheric pressure measurement made proximate to the receiver; and

an atmospheric humidity measurement made proximate to the receiver;

wherein the at least one processor is further adapted to support a hypothesized fault model for at least one of;

a temperature measuring device;

a pressure measuring device; and

a humidity measuring device; and

wherein he at least one processor further adapted to output a probabilistic estimate of a fault for the at least one of;

a temperature measuring device;

a pressure measuring device, and a humidity measuring device.

26. The apparatus of claim 12 wherein the apparatus further comprises a barometric pressure altitude measuring device, and the at least one processor is further adapted to support a hypothesized fault model of the output of the measurement device;

and the at least one processor is further adapted to output a probabilistic estimate of a fault in the output of the measurement device.

27. The apparatus of claim 26 wherein the apparatus further comprises a temperature sensor providing at least one measurement of temperature made proximate to the receiver, a static atmospheric pressure sensor providing at least one measurement of static atmospheric pressure made proximate to the receiver, and an atmospheric humidity sensor providing at least one measurement of atmospheric humidity made proximate to the receiver and wherein the at least one processor is further adapted to support a hypothesized fault model for at least one of:

at least one temperature measurement, the at least one static atmospheric pressure measurement, and the at least one atmospheric humidity measurement; and

wherein the at least one processor is further adapted to output a probabilistic estimate of a fault in the measurement

28. The apparatus of claim 12 wherein the apparatus is further comprising a global positioning satellite (GPS) measuring device having one or more tracking loops for tracking one or more global positioning satellite signals and providing output from a discriminator function within each of the one or more tracking loops for each satellite tracked used as a measurement;

and wherein the at least one processor is further adapted to support a hypothesized fault model for at least one of the measurements and the at least one processor is further adapted to output a probabilistic estimate of a fault in the measurement.

29. The apparatus of claim 28 wherein the at least one processor is further adapted to:

construct an annihilator for removing an unaffected portion of the system state of the recursive stochastic filter,

annihilate the unaffected portion of the system state of the recursive stochastic filter, and

estimate a fault-free history based on the unaffected portion of the system state of the recursive stochastic filter; and

output a fault free estimate.

30. The apparatus of claim 28 wherein the at least one processor is further adapted to execute an adaptive filter structure to estimate channel bias and noise level power spectral density.

31. The apparatus of claim 29 wherein the at least one processor is further adapted to generate a fault free estimate for generating a feedback command to an operably coupled numerically controlled oscillator, wherein the numerically controlled oscillator is operably coupled to the at least one tracking loop.

32. The apparatus of claim 28 wherein each tracking loop of the at least one tracking loop is selected from the group of tracking loops consisting of:

(a) a frequency tracking loop and (b) a code phase and carrier phase tracking loop.

33. The apparatus of claim 29 wherein the at least one processor is further adapted to generate a fault free estimate for generating a feed back command to the GPS receiver reference oscillator for controlling the oscillator frequency.

34. The apparatus of claim 29 wherein the at least one processor is further adapted to generate a fault free estimate for generating a feed back command to the GPS receiver amplifier for controlling the received signal strength.

35. The apparatus of claim 28 wherein the apparatus is further adapted to include a global positioning satellite (GPS) measuring device having at least one of:

a Linear Minimum Variance code tracking process and a Linear Minimum Variance carrier tracking process, for tracking one or more GPS signals and for providing outputs associated with a tracking error for each of a plurality of satellites tracked, from within each of the one or more tracking loops for each satellite tracked, wherein each tracking error may be used as a measurement; and

the at least one processor is further adapted to support a hypothesized fault model for at least one of the measurements and the at least one processor is further adapted output a probabilistic estimate of a fault in the measurement.

36. The apparatus of claim 35 wherein the at least one processor is further adapted to:

construct an annihilator for removing an unaffected portion of the system state of the recursive stochastic filter,

annihilate the unaffected portion of the system state of the recursive stochastic filter, and

estimate a fault-free history based on the unaffected portion of the system state of the recursive stochastic filter; and

output a fault free estimate.

37. The apparatus of claim 35 wherein the at least one processor is further adapted to execute an adaptive filter structure to estimate channel bias and noise level power spectral density.

38. The apparatus of claim 36 wherein the at least one processor is further adapted to generate a fault free estimate for generating a feedback command to an operably coupled numerically controlled oscillator, wherein the numerically controlled oscillator is operably coupled to the at least one tracking loop.

39. The apparatus of claim 36 wherein the at least one processor is further adapted to generate a fault free estimate for generating a feed back command to the GPS receiver reference oscillator for controlling the oscillator frequency.

40. The apparatus of claim 36 wherein the at least one processor is further adapted to generate a fault free estimate for generating a feed back command to the GPS receiver amplifier for controlling the received signal strength.

41. The apparatus of claim 12 wherein the apparatus further comprises at least one acceleration measuring device, and the at least one processor is further adapted to support a hypothesized fault model of the measurement and the at least one processor is further adapted to output a probabilistic estimate of a fault in the measurement.

42. The apparatus of claim 12 wherein the apparatus further comprises at least one angular rate measuring device, and the at least one processor is further adapted to support a hypothesized fault model of the measurement and the at least one processor is further adapted to output a probabilistic estimate of a fault in the measurement.

43. The apparatus of claim 12 wherein the apparatus further comprises at least one magnetic-heading-determining device sensitive in at least one body axis and adapted to provide magnetic heading measurements in the at least one body axis;

and the at least one processor further adapted to support a hypothesized fault model of the measurement and the at least one processor further adapted to output a probabilistic estimate of a fault in the measurement.

44. The apparatus of claim 12 wherein the apparatus further comprises one or more additional global positioning satellite (GPS) receiving devices, wherein each additional GPS receiving device is disposed apart from the first GPS receiving device with each additional GPS receiving device providing at least one time output and at least one of:

at least one position output;

at least one velocity output;

at least one pseudorange output;

at least one pseudorange rate output; and

at least one carrier phase output; and

the at least one processor further adapted to support a hypothesized fault model of the measurement and the at least one processor further adapted to output a probabilistic estimate of a fault in the measurement.

45. The apparatus of claim 12 wherein the apparatus is operably coupled with a vehicle wherein the vehicle has one or more actuators and wherein the apparatus is adapted to receive a plurality of commands transmitted to the one or more vehicle actuators and the one or more processors are adapted to support:

a dynamic system model of the vehicle motion as a function of the one or more vehicle actuators;

a hypothesized fault model of at least one of;

the at least one vehicle actuator and a dynamic model; and

and the one or more processors are adapted to output a probabilistic estimate of a fault in at least one of;

the at least one vehicle actuator and the dynamic model.

46. A system for performing fault tolerant navigation comprising:

a first global positioning satellite (GPS) receiver providing at least one position outputs and at least one time output;

an acceleration-determining device sensitive in at least three axes capable of providing acceleration measurements in at least three axes;

an angular rate measuring device sensitive in at least three axes capable of providing angular rates of rotation in at least three axes; and

at least one processor adapted to support a dynamic system model of the error propagation of the integrated acceleration determining devices and angular rate measuring devices and a hypothesized fault model for any or all of the acceleration determining devices and angular rate measuring devices;

the at least one processor further adapted to;

determine a fault-free residual from a residual process by operating on an updated recursive stochastic filter state estimation residual with a projection model;

determine a first probabilistic estimate of a fault from;

at least one projected recursive stochastic filter state estimation residual;

at least one measurement model, and at least one hypothesized first fault model, wherein the determining of a first probabilistic estimate of a fault is based on at least one of;

a Multiple Hypothesis Wald Sequential Probability Ratio Test; and

a Multiple Hypothesis Shiryayev Sequential Probability Ratio test;

testing for a fault based on the determined probabilistic estimate of a fault; and

outputting at least one of;

at least one probabilistic estimate of a fault and at least one fault free estimate.

47. A system for performing fault tolerant navigation of a plurality of vehicles comprising:

at least one primary vehicle;

at least one secondary vehicle;

a transmitter for transmitting the derived secondary vehicle fault free state estimate solutions; and

a receiver for receiving the transmitted derived fault free state estimate solution and measurements; and

at least one processor for deriving a primary-relative fault free state estimate solution for the secondary vehicle wherein the processor receiving at least one of;

a plurality of measurements of the one or more vehicle sensors, state estimators, or actuators and a plurality of commands transmitted to the one or more vehicle actuators;

and in a recursive stochastic filter having a vehicle-specific dynamic system model as a function of the one or more vehicle actuators;

determining a fault-free residual from a residual process by operating on an updated recursive stochastic filter state estimation residual with a projection model;

determining a first probabilistic estimate of a fault from;

at least one projected recursive stochastic filter state estimation residual;

at least one measurement model, and at least one hypothesized first fault model, wherein the determining of a first probabilistic estimate of a fault is based on at least one of;

a Multiple Hypothesis Wald Sequential Probability Ratio Test; and

a Multiple Hypothesis Shiryayev Sequential Probability Ratio test;

testing for a fault based on the determined probabilistic estimate of a fault;

estimating a fault direction model; and

outputting a fault-free state estimate.

48. The system of claim 47 wherein the at least one processor is further adapted to output the fault free state estimate of the at least one secondary vehicle in relation to the at least one primary vehicles.

49. A system for performing fault tolerant navigation of a plurality of vehicles of claim 47 wherein the recursive filter includes a global differential Extended Kalman Filter.

50. A system for performing fault tolerant navigation of a plurality of vehicles of claim 47 wherein the recursive filter includes a decentralized differential Extended Kalman Filter.

51. A system of claim 47 wherein the system executes a kinematic carrier phase integer ambiguity estimation algorithm to determine the GPS integer ambiguity using the carrier phase measurements wherein the processor directs the outputs and measurements of the kinematic carrier phase integer ambiguity estimation algorithm to output the fault free state estimate of the at least one secondary vehicle in relation to the at least one primary vehicles.

52. A system of claim 51 wherein the kinematic carrier phase integer ambiguity estimation algorithm is a Wald Test

53. A system of claim 52 wherein the kinematic carrier phase integer ambiguity estimation algorithm transitions to the Shiryayev Test for the purposes of monitoring and correcting the integer ambiguity estimates.

54. The system of claim 47 further comprising:

at least one generalized relative range-determining device, sensitive on the at least one primary vehicle in at least one body axis, adapted to provide relative range measurements in the at least one body axis,

at least one target having at least one target location reference point on a secondary vehicle;

a hypothesized fault model for at least one of the generalized relative range determining devices,

the at least one processor adapted to provide a plurality of state estimates wherein the at least one processor directs the outputs and measurements to output the fault free state estimate utilizing the output of the at least one generalized relative range determining devices as measurements.