Fault-tolerant system, apparatus and method

• US 20050114023A1
• Filed: 11/24/2004
• Published: 05/26/2005
• Est. Priority Date: 11/26/2003
• Status: Abandoned Application

• Current Assignee: Dale L. Cooper, Jason Lee Speyer, Walton Ross Williamson
• Original Assignee: Dale L. Cooper, Jason Lee Speyer, Walton Ross Williamson
• Inventors: Cooper, Dale L., Speyer, Jason Lee, Williamson, Walton Ross
• Application Number:
  US10/997,192
• Publication Number:
  US 20050114023A1
• Time in Patent Office: Days
• US Class Current: 701/214
• CPC Class Codes: B64D 39/00 Refuelling during flight filling or emptying fuel tanks B64D37/14
• CPC Class Codes: G01C 21/1656 with passive imaging devices, e.g. cameras
• CPC Class Codes: G01C 21/188 for accumulated errors, e.g. by coupling inertial systems with absolute positioning 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
• CPC Class Codes: G05D 1/104 involving a plurality of aircrafts, e.g. formation flying traffic control systems for aircraft G08G5/00

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 of integrity maintenance in an estimating processor including at least one system state having an estimable value, at least one dynamic system model responsive to changes in the at least one system state and receptive to one or more external inputs, a measurement model comprising at least one measurement having information pertaining to the at least one system state, and at least one hypothesized fault model, wherein the at least one hypothesized fault model describes a direction in which a fault may act on any of the at least one system state, the method comprising the steps of:

(a) determining a residual by differencing the at least one system state and the at least one measurement;

(b) projecting at least one hypothesized fault model;

(c) determining a fault-free residual by applying the at least one projected hypothesized fault to the determined residual;

(d) determining a probabilistic estimate of fault occurrence using the at least one projected hypothesized fault model and the at least one measurement based on results of or one or more residual testing wherein the one or more residual tests are selected from the group consisting of;

Multiple Hypothesis Wald Sequential Probability Ratio residual testing, Multiple Hypothesis Shiryayev Sequential Probability Ratio residual testing and Chi-Square Test residual testing;

(e) updating a filter gain;

(f) updating the at least one system state with a product of the updated filter gain and the determined residual of step (a);

(g) determining fault occurrence based on the determined probabilistic estimate; and

(h) predicting a next at least one system state using the updated at least one system state and the at least one dynamic system model and

(i) updating and predicting the at least one fault direction using the at least one dynamic system model.

2. The method of integrity maintenance as claimed in claim 1 wherein the step of determining a probabilistic estimate of fault occurrence includes the steps of Wald Sequential Probability Ratio residual testing followed by the steps of Shiryayav Sequential Probability Ratio residual testing.

3. The method of integrity maintenance as claimed in claim 1 wherein the step of determining a probabilistic estimate includes Multiple Hypothesis Shiryayav Sequential Probability Ratio testing wherein one or more probability estimates are re-initialized according to the determined probabilistic estimate of fault occurrence.

4. The method of integrity maintenance as claimed in claim 1 wherein a determination of fault occurrence invokes a step of restarting the method and providing one or more system states of a reduced order.

5. The method of integrity maintenance as claimed in claim 1 wherein:

(a) the at least one dynamic system model represents a static parameter system;

(b) the at least one measurement has associated statistical error uncertainty represented by a measurement noise covariance and

(c) the step of updating the filter gain uses a portion of the measurement noise covariance and the at least one measurement; and

(d) the step of determining the probabilistic estimate of fault occurrence uses knowledge of the measurement noise covariance.

6. The method of integrity maintenance as claimed in claim 1 wherein the at least one hypothesized fault model comprises one or more nuisance fault models and one or more target fault models.

7. The method of integrity maintenance as claimed in claim 1 further including the step of adaptively estimating a measurement noise covariance using an output history of determined residual.

8. The method of integrity maintenance as claimed in claim 1 further including the steps of:

removing a portion of the system state unaffected by a specific fault direction as output of the step of determining a residual and

estimating a fault time history based on the removed portion of the system state.

9. A system for performing fault tolerant navigation comprising:

a global positioning satellite receiving device providing at least three position outputs, or pseudorange measurements, and an associated time output;

a processor for providing a plurality of state estimates by taking in the pseudorange measurements and associated time output wherein the processor comprises;

a minimum variance estimator of state estimates;

a sensor fault detecting module adapted to execute residual testing steps based on one or more testing steps selected from the group consisting of;

Multiple Hypothesis Wald Sequential Probability Ratio residual testing, Multiple Hypothesis Shiryayev Sequential Probability Ratio residual testing and the Chi-Square Test residual testing; and

a sensor fault annihilator module adapted to estimate a fault time history and remove the estimated fault time history from the state estimates.

10. The system for performing fault tolerant navigation as claimed in claim 9 further comprising:

an effecter, or actuator, fault detecting module adapted to execute Wald Sequential Probability Ratio residual testing integrally with the sensor fault detecting module; and

an effecter, or actuator, fault annihilator module adapted to estimate a fault time history and remove the estimated fault time history from the state estimates.

11. The system for performing fault tolerant navigation as claimed in claim 9 further comprising:

(a) an acceleration determining device sensitive in at least three axes capable of providing acceleration measurements in at least three axes;

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

(c) a process further adapted to receive the provided acceleration measurements and acceleration measurement.

12. The system for performing fault tolerant navigation as claimed in claim 11 wherein:

(a) the global positioning satellite receiving device is further adapted to use a tracking loop process to track the global positioning satellite signals and provide output from a discriminator function for each satellite tracked; and

(b) the processor is further adapted to;

receive the receive outputs and sensor measurements and itself output a fault free state estimate utilizing the output of the discriminator functions as additional measurements; and

to provide the fault free estimate to the tracking loop process.

13. A system for autonomous relative navigation comprising:

(a) a target element, comprising;

(i) at least one target element global positioning system antenna;

(ii) at least one target element global positioning system receiver operably coupled to the at least one target element global positioning system antenna;

(iii) a target element processor for deriving a position, velocity, attitude solution for the target element; and

(iv) a transmitter for transmitting the derived target position, velocity, attitude solution as well as global positioning system measurements from any of the at least one global positioning system receivers; and

(b) a seeker element comprising;

(i) at least one seeker element global positioning system antenna;

(ii) at least one seeker element global positioning system receiver operably coupled to the at least one seeker global positioning system antenna; and

(iii) a receiver for receiving the transmitted derived target position, velocity, attitude solution and global positioning system measurements; and

(iv) a seeker element processor for deriving a seeker-relative position, velocity, attitude solution for the target element;

wherein the target element processor and seeker element processor each comprise;

a minimum variance estimator of state estimates;

a sensor fault detecting module adapted to execute residual testing steps based on one or more testing steps selected from the group consisting of;

Multiple Hypothesis Wald Sequential Probability Ratio residual testing, Multiple Hypothesis Shiryayev Sequential Probability Ratio residual testing and the Chi-Square Test residual testing; and

a sensor fault annihilator module adapted to estimate a fault time history and remove the estimated fault time history from the state estimates.

14. The system for autonomous relative navigation as claimed in claim 13 wherein the target element further comprises an inertial measurement unit operably coupled to the target element processor for deriving a position, velocity, and attitude solution for the target element.

15. The system for autonomous relative navigation as claimed in claim 13 wherein the target element further comprises a magnetometer operably coupled to the target element processor for refining a position, velocity, attitude solution for the target element.

16. The system for autonomous relative navigation as claimed in claim 13 wherein the target element further comprises a vision-based instrument operably coupled to the target element processor and adapted to provide measurements for deriving a seeker-relative position, velocity, and attitude solution for the target element.

17. The system for autonomous relative navigation as claimed in claim 13, wherein the target element processor is further adapted to determine the position, velocity, attitude solution of the target and use the solution to direct the processing of any global positioning system receiver tracking loops within the target.

18. The system for autonomous relative navigation as claimed in claim 13 wherein the seeker element processor is adapted to apply a Wald test to the received target transmissions of global positioning system carrier phase measurements for use in deriving a seeker-relative position, velocity, attitude solution for the target element.

19. The system for autonomous relative navigation as claimed in claim 13 wherein the seeker element further comprises an inertial measurement unit operably coupled to the seeker element processor for deriving a seeker-relative position, velocity, attitude solution for the target element.

20. The system for autonomous relative navigation as claimed in claim 13 wherein the seeker element further comprises a magnetometer unit operably coupled to the seeker element processor for deriving a seeker-relative position, velocity, attitude solution for the target element.

21. The system for autonomous relative navigation as claimed in claim 13 wherein the seeker element further comprises a vision-based instrument operably coupled to the seeker target processor and provides measurements for deriving a seeker-relative position, velocity, attitude solution for the target element.

22. The system for autonomous relative navigation as claimed in claim 13 wherein the seeker element further comprises a system of measuring vehicle control system outputs operably coupled to the seeker element processor for deriving the seeker or seeker-relative position, velocity, attitude solution for the target element.

23. The system for autonomous relative navigation as claimed in claim 13 wherein the seeker processor further determines a seeker-relative position, velocity, attitude solution and uses the solution in the processing of global positioning system receiver tracking loops.

24. An apparatus for maintaining state estimation integrity, the apparatus including at least one system state having an estimable value, at least one dynamic system model responsive to changes in the at least one system state and receptive to one or more external inputs;

a measurement model comprising at least one measurement having information pertaining to the at least one system state, and at least one hypothesized fault model, wherein the at least one hypothesized fault model describes a direction in which a fault may act on any of the at least one system state, the apparatus further comprising;

means for determining a residual by differencing the at least one system state and the at least one measurement;

means for projecting at least one hypothesized fault model;

means for updating a filter gain;

means for updating the at least one system state with a product of the updated filter gain and the determined residual;

means for determining the residual by differencing the at least one updated system state and the at least one measurement;

means for determining a fault-free residual by applying the at least one projected hypothesized fault to update the determined residual;

means for determining a probabilistic estimate of fault occurrence using the projected at least one hypothesized fault model and the at least one measurement;

means for determining fault occurrence based on the determined probabilistic estimate;

means for predicting a next at least one system state using the updated at least one system state and the at least one dynamic system model; and

means for updating and predicting the at least one fault direction using the at least one dynamic system model.