Method to improve leveling performance in navigation systems

Patent metadata

Field	Value
Publication number	US-10444017-B2
Application number	US-201213464298-A
Country	US
Kind code	B2
Filing date	May 4, 2012
Priority date	Oct 25, 2011
Publication date	Oct 15, 2019
Grant date	Oct 15, 2019

Abstract

An attitude estimator system is provided. The attitude estimator system includes a navigation system, a Kalman filter, and a form observations module. The navigation system receives input from a first accelerometer and gyroscope, a second accelerometer and gyroscope, and a third accelerometer and gyroscope. The form observations module receives input from at least one high performance accelerometer and/or gyroscope; forms and outputs at least one of velocity-derived observations and attitude-derived observations. The Kalman filter processes by at least one of: inputting the velocity-derived observations formed in the form observations module, rotating the velocity-derived observation into a sensor-frame, and zeroing gains associated with at least one low performance accelerometer and/or gyroscope; or inputting the attitude-derived observations that are based on output from at least one of the first high performance accelerometer, the first high performance gyroscope, and the second high performance accelerometer.

First claim

What is claimed is:

1. A method to improve performance of a navigation system communicatively coupled to a first high performance accelerometer and a first high performance gyroscope aligned to a first sensor-frame-level axis, a second high performance accelerometer and a second gyroscope aligned to a second sensor-frame-level axis, and a third low performance accelerometer and a third low performance gyroscope aligned to a third sensor frame axis, the method comprising:
computing at least one observation based on input to a form observations module from at least one of the first high performance gyroscope, the first high performance accelerometer, and the second high performance accelerometer;
outputting the at least one observation to a Kalman filter from the form observations module; inputting observations formed in the form observations module at a module in the Kalman filter to rotate an error into a sensor-frame;
rotating the observation into the sensor-frame;
zeroing selected gains associated with at least one of the third low performance accelerometer and the third low performance gyroscope at a compute Kalman gains module in the Kalman filter; and
outputting error corrections as Kalman filter feedback from the Kalman filter to the navigation system, wherein the navigation system updates a navigation solution based on the Kalman filter feedback.

2. The method of claim 1 , wherein the form observations module includes a compute reference attitude module and a module to form attitude observation, wherein computing the at least one observation based on input to the form observations module comprises:
computing a reference attitude direction cosine matrix at the compute reference attitude module based on data from at least one of the first high performance accelerometer, the first high performance gyroscope, and the second high performance accelerometer;
inputting the reference attitude direction cosine matrix at the module to form attitude observation in the form observations module; and
computing an attitude observation at the module to form attitude observation, and wherein outputting at least one observation to the Kalman filter comprises:
outputting the attitude observation to the Kalman filter from the module to form attitude observation.

3. The method of claim 2 , wherein the form observations module further includes a compute velocity observation module, wherein the computing the at least one observation further comprises:
differencing a navigation velocity from the navigation system and a reference velocity value, and wherein outputting at least one observation to the Kalman filter further comprises:
outputting a velocity observation to the Kalman filter from the compute velocity observation module.

4. The method of claim 1 , wherein the form observations module includes a compute velocity observation module, wherein the computing the at least one observation based on input to a form observations module comprises:
differencing a navigation velocity from the navigation system and a reference velocity value, and wherein outputting at least one observation to the Kalman filter comprises:
outputting a velocity observation to the Kalman filter from the compute velocity observation module.

5. The method of claim 1 , wherein the form observations module is a compute attitude observation module comprising a first module, a second module, and a third module, the method further comprising:
computing a reference roll value and a reference pitch value based on input to the first module from the first high performance accelerometer and the second high performance accelerometer;
computing a reference attitude value based on input to the second module from the first high performance gyroscope;
outputting a reference heading value from the third module; and
differencing a navigation heading from the navigation system and the reference heading value from the third module at a form observations module, wherein outputting the at least one observation to the Kalman filter comprises:
outputting an attitude observation from the form observations module to the Kalman filter.

6. A program product for improving performance of a navigation system communicatively coupled to a first high performance accelerometer and a first high performance gyroscope aligned to a first body-frame-level axis, a second high performance accelerometer and a second gyroscope aligned to a second body-frame-level axis, a third low performance accelerometer and a third low performance gyroscope aligned to a third body-frame axis, the program-product comprising a non-transitory processor-readable medium on which program instructions are embodied, wherein the program instructions are operable, when executed by at least one processor included in an attitude estimator system communicatively coupled to the navigation system, to cause the attitude estimator system to:
compute at least one observation based on input to a form observations module from at least one of the first high performance gyroscope, the first high performance accelerometer, and the second high performance accelerometer;
output the at least one observation to a Kalman filter from the form observations module; input observations formed in the form observations module at a module in the Kalman filter to rotate an error into a sensor-frame;
rotate the observation into the sensor-frame;
zero selected gains associated with at least one of the third low performance accelerometer and the third low performance gyroscope at a compute Kalman gains module in the Kalman filter; and
output error corrections as Kalman filter feedback from the Kalman filter to the navigation system, wherein the navigation system updates a navigation solution based on the Kalman filter feedback.

7. The program product of claim 6 , wherein the form observations module includes a compute reference attitude module and a module to form attitude observation, wherein the program instructions are further operable, when executed by the at least one processor included in the attitude estimator system communicatively coupled to the navigation system, to cause the attitude estimator system to:
compute a reference attitude direction cosine matrix at the compute reference attitude module based on data from at least one of the first high performance accelerometer, the first high performance gyroscope, and the second high performance accelerometer;
input the reference attitude direction cosine matrix at the module to form attitude observation in the form observations module; and
compute an attitude observation at the module to form attitude observation.

8. The program product of claim 7 , wherein the form observations module further includes a compute velocity observation module, wherein the program instructions are further operable, when executed by the at least one processor included in the attitude estimator system communicatively coupled to the navigation system, to cause the attitude estimator system to:
difference a navigation velocity from the navigation system and a reference velocity value, wherein the outputting the at least one observation to the Kalman filter comprises:
output a velocity observation to the Kalman filter from the compute velocity observation module.

9. The program product of claim 6 , wherein the form observations module includes a compute velocity observation module, wherein the program instructions are further operable, when executed by the at least one processor included in the attitude estimator system communicatively coupled to the navigation system, to cause the attitude estimator system to:
difference a navigation velocity from the navigation system and a reference velocity value, wherein output

Assignees

• Bye Charles T
• Liu Fan
• Morgan Kenneth Steven
• Honeywell Int Inc

Inventors

• Bye Charles T
• Liu Fan
• Morgan Kenneth Steven

Classifications

• G01C21/16 Primary

  by integrating acceleration or speed, i.e. inertial navigation · CPC title

• G01C21/183 Primary

  Compensation of inertial measurements, e.g. for temperature effects · CPC title