Measurement fault detection

• US 7,356,445 B2
• Filed: 12/15/2003
• Issued: 04/08/2008
• Est. Priority Date: 08/28/2000
• Status: Expired due to Fees

• Current Assignee: CSR Technology Incorporated (Qualcomm, Inc.)
• Original Assignee: SIRF Technology Incorporated (Qualcomm, Inc.)
• Inventors: Brodie, Keith Jacob
• Primary Examiner(s): Barlow; John
• Assistant Examiner(s): Le; John
• Application Number:
  US10/737,702
• Publication Number:
  US 20040199833A1
• Time in Patent Office: 1,576 Days
• Field of Search: 702/59, 702/97, 702/116, 702/183, 702/185, 702/190, 701/213, 701/215, 701/216, 342/357.02, 342/358, 370/329
• US Class Current: 702/185
• CPC Class Codes: G01S 19/20 Integrity monitoring, fault detection or fault isolation of space segment
• CPC Class Codes: G01S 19/22 Multipath-related issues
• CPC Class Codes: G01S 19/396 Determining accuracy or reliability of position or pseudorange measurements
• CPC Class Codes: G01S 19/42 Determining position
• CPC Class Codes: G01S 5/021 Calibration, monitoring or correction G01S5/0252 takes precedence
• CPC Class Codes: G01S 5/0294 Trajectory determination or predictive filtering, e.g. target tracking or Kalman filtering

Abstract

The present invention discloses a method and an apparatus for improving measurement fault detection in a sequential measurement processing estimator, and is particularly applied to Global Positioning Receivers.

Claims

1. A measurement fault detection system in a sequential measurement processing estimator, the measurement fault detection system comprising:

a plurality of measurements, each measurement having an associated measurement time;

a sorter that sorts the plurality of measurements in order of increasing fault probability;

a variable-gain filter in signal communication with the sorter;

an estimate of each of the plurality of measurements generated by the variable-gain filter, wherein each estimate includes a state matrix and a covariance matrix propagated forward or backward in time from the time of the measurement with a next lowest fault probability in response to the time of the measurement with the next lowest fault probability being earlier or later, respectively, than the time of the measurement for which the estimate is then being generated; and

a state matrix and a covariance matrix propagated forward from the time of the measurement with a highest fault probability to a reporting time.

2. The measurement fault detection system of claim 1, wherein the variable-gain filter is a Kalman filter.

3. The measurement fault detection system of claim 2, wherein the plurality of measurements is received at a Global Positioning System (GPS) receiver.

4. The measurement fault detection system of claim 1, wherein the measurements are non-simultaneous.

5. An apparatus for measuring fault detection, the apparatus comprising:

means for recording a plurality of measurements, each measurement having an associated measurement time;

means for sorting the plurality of measurements, wherein the sort of the plurality of measurements is performed in order of increasing fault probability;

means for propagating a state matrix and a covariance matrix forward from a first time to the time of the measurement having a lowest fault probability;

means for processing the measurement having the lowest fault probability first, wherein the processing comprises;

means for updating the state matrix and the covariance matrix at the time of the measurement having the lowest fault probability; and

means for propagating the state matrix and the covariance matrix backwards or forwards in time to the time of the measurement with a next highest fault probability in response to the time of the measurement with the next highest fault probability being earlier or later, respectively, than the time of the measurement with a then lowest fault probability;

means for continuing processing until all measurements have been processed; and

means for propagating the state matrix and the covariance matrix forward from the time of the measurement with a highest fault probability to a reporting time.

6. The apparatus of claim 5, wherein the apparatus is operatively connected to a Global Positioning System (GPS) receiver.

7. The apparatus of claim 6, wherein the means for propagating the state matrix and covariance matrix backwards in time further includes means for subtracting a process noise matrix from a state error covariance matrix.

8. The apparatus of claim 7, wherein the measurements are non-simultaneous.

9. A machine-readable medium that contains instructions for implementing a method of fault detection, the instructions implementing the method steps comprising:

recording a plurality of measurements, each measurement having an associated measurement time;

sorting the plurality of measurements, wherein the sort of the plurality of measurements is performed in order of increasing fault probability;

propagating a state matrix and a covariance matrix forward from a first time to the time of the measurement having a lowest fault probability;

processing the measurement having the lowest fault probability first, wherein the processing comprises;

updating the state matrix and the covariance matrix at the time of the measurement having the lowest fault probability; and

propagating the state matrix and the covariance matrix backwards or forwards in time to the time of the measurement with a next highest fault probability in response to the time of the measurement with the next highest fault probability being earlier or later, respectively, than the time of the measurement with a then lowest fault probability;

continuing processing until all measurements have been processed; and

propagating the state matrix and the covariance matrix forward from the time of the measurement with a highest fault probability to a reporting time.

10. The machine-readable medium that contains instructions for implementing a method of fault detection of claim 9, wherein the machine-readable medium is operatively connected to a Global Positioning System (GPS) receiver.

11. The machine-readable medium that contains instructions for implementing a method of fault detection of claim 10, wherein the method step of propagating the state matrix and covariance matrix backwards in time further includes subtracting a process noise matrix from a state error covariance matrix.

12. The machine-readable medium that contains instructions for implementing a method of fault detection of claim 11, wherein the measurements are non-simultaneous.