Estimation of N-dimensional parameters while sensing fewer than N dimensions

• US 8,812,235 B2
• Filed: 02/08/2012
• Issued: 08/19/2014
• Est. Priority Date: 02/13/2011
• Status: Expired due to Fees

• Current Assignee: Honeywell International Inc.
• Original Assignee: Honeywell International Inc.
• Inventors: Ingvalson, Ryan, Hawkinson, Wesley J., McCroskey, Robert C., Samanant, Paul
• Primary Examiner(s): Zanelli, Michael J
• Application Number:
  US13/368,823
• Publication Number:
  US 20120209520A1
• Time in Patent Office: 923 Days
• Field of Search: None
• US Class Current: 701/507
• CPC Class Codes: G01C 21/1652 with ranging devices, e.g. LIDAR or RADAR
• CPC Class Codes: G01C 21/1654 with electromagnetic compass
• CPC Class Codes: G01C 21/188 for accumulated errors, e.g. by coupling inertial systems with absolute positioning systems

Abstract

Embodiments of the present invention provide improved systems and methods for estimating N-dimensional parameters while sensing fewer than N dimensions. In one embodiment a navigational system comprises a processor and an inertial measurement unit (IMU) that provides an output to the processor, the processor providing a navigation solution based on the output of the IMU, wherein the navigation solution includes a calculation of an n-dimensional parameter. Further, the navigational system includes at most two sensors that provide an output to the processor, wherein the processor computes an estimate of an n-dimensional parameter from the output of the at most two sensors for bounding errors in the n-dimensional parameter as calculated by the processor when the trajectory measured by the IMU satisfies movement requirements, wherein “n” is greater than the number of the at most two sensors.

Claims

1. A navigational system, the system comprising:

at least one processor;

an inertial measurement unit (IMU) that measures a trajectory and provides an output to the at least one processor, the at least one processor providing a navigation solution based on the output of the IMU, wherein the navigation solution includes a calculation of an n-dimensional parameter; and

at most two velocity sensors that provide an output to the at least one processor, wherein the at most two velocity sensors measure velocity in at most two dimensions, wherein the at least one processor computes an estimate of an n-dimensional parameter from the output of the at most two velocity sensors for bounding errors in the n-dimensional parameter as calculated by the at least one processor when the trajectory measured by the IMU causes the at most two velocity sensors to measure motion through n dimensions, wherein “

n”

is greater than the number of dimensions measured simultaneously by the at most two velocity sensors.

2. The navigational system of claim 1, wherein the at most two velocity sensors comprise sensors that measure velocity along a single axis.

3. The navigational system of claim 1, further comprising aiding sensors, wherein the aiding sensors provide an output to the at least one processor, the output of the aiding sensors configured to provide an estimate of motion parameters for bounding errors in the navigation solution.

4. The navigational system of claim 3, further comprising a motion classifier that receives the output from a portion of the aiding sensors to provide additional motion information not included in the navigation solution.

5. The navigational system of claim 3, further comprising a Kalman filter that uses a measurement difference calculated by the at least one processor, the measurement difference representing the difference between the motion information derived from the navigation solution and data collected from the at most two velocity sensors and the aiding sensors, wherein the Kalman filter provides navigation corrections to the navigation solution.

6. The navigational system of claim 5, wherein the at least one processor is configured to prefilter the measurement difference calculated by the at least one processor before the measurement difference is used by the Kalman filter.

7. The navigational system of claim 1, wherein the at most two velocity sensors is a single sensor and the at least one processor provides an estimate of a three dimensional parameter when the trajectory satisfies the movement requirement by including motion in at least two of pitch, roll, and yaw where the single sensor provides a sensor measurement along three dimensions.

8. The navigational system of claim 1, wherein the at most two velocity sensors are two sensors and the at least one processor provides an estimate of a three dimensional parameter when the trajectory satisfies the movement requirement by including motion in at least one of pitch, roll, and yaw where the two sensors provide sensor measurements along three dimensions.

9. The navigational system of claim 1, wherein the IMU and the at least two velocity sensors are part of a personal navigation system.

10. A method for bounding motion errors, the method comprising:

calculating a navigation solution for a platform based on measurements from an IMU;

receiving a measurement from at most two velocity sensors, wherein the at most two velocity sensors are used to provide an estimated velocity parameter in less than n dimensions, wherein “

n”

is greater than the number of dimensions measured simultaneously by the at most two velocity sensors;

calculating an estimate of accumulated error for a motion parameter in n dimensions based on the estimated velocity parameter when a trajectory of platform motion causes the at most two velocity sensors to measure motion through n dimensions; and

correcting the motion parameter in n dimensions based on the estimate of accumulated error.

11. The method of claim 10, wherein the at most two velocity sensors provide an estimated velocity measurement in less than n dimensions.

12. The method of claim 10, further comprising using the estimated velocity measurement to correct acceleration measurements by the IMU in n dimensions.

13. The method of claim 10, wherein calculating an estimate of accumulated error is further based on motion information received from aiding sensors.

14. The method of claim 13, wherein the aiding sensors comprise at least one of:

a magnetic sensor;

an altimeter;

a GPS; and

a ranging device.

15. A system for tracking movement, the system comprising

at least one navigation system, wherein the at least one navigation system comprises:

at least one processor;

an inertial measurement unit (IMU) coupled to the at least one processor, the at least one processor providing a navigation solution for a platform based on the output of the IMU, wherein the navigation solution includes a calculation of an n-dimensional motion parameter;

a sensor configured to measure a motion parameter in at most two dimensions,

wherein the at least one processor is further configured to receive the motion parameter from the sensor and provide an estimate of the n-dimensional motion parameter for use in bounding the error of the n-dimensional motion parameter as calculated by the at least one processor when the trajectory measured by the IMU satisfies movement requirements, wherein the estimate is based on the motion parameter and n is greater than the dimensions measured by the sensor; and

a transmitter configured to transmit the navigation solution; and

a base station that receives navigation solutions from the at least one navigation system.

16. The system of claim 15, wherein the sensor measures the motion parameter in one dimension and the navigation solution calculated by the at least one processor includes an estimate of a three dimensional motion parameter when the platform experiences movement in at least two of pitch, roll, and yaw.

17. The system of claim 15, wherein the sensor measures the motion parameter in two dimensions and the navigation solution calculated by the at least one processor includes an estimate of a three dimensional motion parameter when the platform experiences movement in at least one of pitch, roll, and yaw.

18. The system of claim 15, wherein the sensor measures velocity in at most two dimensions.

19. The system of claim 15, wherein the at least one navigation system further comprises aiding sensors, wherein the aiding sensors provide an output to the at least one processor, the output of the aiding sensors configured to provide an estimate of motion parameters for bounding errors in the navigation solution.

20. The system of claim 19, further comprising a motion classifier that receives the output from a portion of the aiding sensors to provide additional motion information not included in the navigation solution.