Multi-inertial measurement unit fusion for fine-resolution position estimation

Patent metadata

Field	Value
Publication number	US-11435485-B2
Application number	US-202117437389-A
Country	US
Kind code	B2
Filing date	May 14, 2021
Priority date	May 22, 2020
Publication date	Sep 6, 2022
Grant date	Sep 6, 2022

Abstract

A method comprises: obtaining a GPS measurement; obtaining a first IMU measurement; obtaining a second IMU measurement; applying a first particle filter to the GPS measurement and the first IMU measurement to obtain a first position solution; applying a second particle filter to the GPS measurement and the second IMU measurement to obtain a second position solution; calculating a first sensor weight of the first position solution based on a likelihood function; calculating a second sensor weight of the second position solution based on the likelihood function; resampling the first position solution based on the first sensor weight to obtain a first resampled position solution; resampling the second position solution based on the second sensor weight to obtain a second resampled position solution; and calculating a final position estimate based on the GPS measurement, the first resampled position solution, and the second resampled position solution.

First claim

What is claimed is:

1. A method comprising:
obtaining a Global Positioning System (GPS) measurement;
obtaining a first inertial measurement unit (IMU) measurement;
obtaining a second IMU measurement;
applying a first particle filter to the GPS measurement and the first IMU measurement to obtain a first position solution;
applying a second particle filter to the GPS measurement and the second IMU measurement to obtain a second position solution;
calculating a first sensor weight of the first position solution based on a likelihood function;
calculating a second sensor weight of the second position solution based on the likelihood function;
resampling the first position solution based on a sum of the first sensor weight and the second sensor weight to obtain a first resampled position solution;
resampling the second position solution based on the second sensor weight to obtain a second resampled position solution; and
calculating a final position estimate based on the GPS measurement, the first resampled position solution, and the second resampled position solution.

2. The method of claim 1 , wherein the first particle filter is based on a first probability distribution function (PDF), and wherein the second particle filter is based on a second PDF.

3. The method of claim 1 , wherein the likelihood function determines a first likelihood of the first position solution compared to the GPS measurement and a second likelihood of the second position solution compared to the GPS measurement.

4. The method of claim 1 , wherein calculating the first sensor weight comprises calculating the first sensor weight based on a probability density function (PDF).

5. The method of claim 4 , wherein calculating the second sensor weight comprises calculating the second sensor weight based on the PDF.

6. The method of claim 1 , wherein resampling the second position solution comprises resampling the second position solution based on the sum.

7. The method of claim 1 , wherein resampling the first position solution and the second position solution comprises resampling the first position solution and the second position solution at a rate between about 1 kilohertz (kHz) and about 4 kHz.

8. An apparatus comprising:
a memory; and
a processor coupled to the memory and configured to:
obtain a Global Positioning System (GPS) measurement;
obtain a first inertial measurement unit (IMU) measurement;
obtain a second IMU measurement;
apply a first particle filter to the GPS measurement and the first IMU measurement to obtain a first position solution;
apply a second particle filter to the GPS measurement and the second IMU measurement to obtain a second position solution;
calculate a first sensor weight of the first position solution based on a likelihood function;
calculate a second sensor weight of the second position solution based on the likelihood function;
resample the first position solution based on a sum of the first sensor weight and the second sensor weight to obtain a first resampled position solution;
resample the second position solution based on the second sensor weight to obtain a second resampled position solution; and
calculate a final position estimate based on the GPS measurement, the first resampled position solution, and the second resampled position solution.

9. The apparatus of claim 8 , wherein the first particle filter is based on a first probability distribution function (PDF), and wherein the second particle filter is based on a second PDF.

10. The apparatus of claim 8 , wherein the likelihood function determines a first likelihood of the first position solution compared to the GPS measurement and a second likelihood of the second position solution compared to the GPS measurement.

11. The apparatus of claim 8 , wherein the processor is further configured to calculate the first sensor weight based on a probability density function (PDF).

12. The apparatus of claim 11 , wherein the processor is further configured to calculate the second sensor weight based on the PDF.

13. The apparatus of claim 8 , wherein the processor is further configured to resample the second position solution based on the sum.

14. The apparatus of claim 8 , wherein the processor is further configured to resample the first position solution and the second position solution at a rate between about 1 kilohertz (kHz) and about 4 kHz.

15. A computer program product comprising instructions that are stored on a non-transitory medium and that, when executed by a processor, cause an apparatus to:
obtain a Global Positioning System (GPS) measurement;
obtain a first inertial measurement unit (IMU) measurement;
obtain a second IMU measurement;
apply a first particle filter to the GPS measurement and the first IMU measurement to obtain a first position solution;
apply a second particle filter to the GPS measurement and the second IMU measurement to obtain a second position solution;
calculate a first sensor weight of the first position solution based on a likelihood function;
calculate a second sensor weight of the second position solution based on the likelihood function;
resample the first position solution based on a sum of the first sensor weight and the second sensor weight to obtain a first resampled position solution;
resample the second position solution based on the second sensor weight to obtain a second resampled position solution; and
calculate a final position estimate based on the GPS measurement, the first resampled position solution, and the second resampled position solution.

16. The computer program product of claim 15 , wherein the likelihood function determines a first likelihood of the first position solution compared to the GPS measurement and a second likelihood of the second position solution compared to the GPS measurement.

17. The computer program product of claim 15 , wherein the instructions, when executed by the processor, further cause the apparatus to resample the second position solution based on the sum.

18. The computer program product of claim 15 , wherein the first particle filter is based on a first probability distribution function (PDF), and wherein the second particle filter is based on a second PDF.

19. The computer program product of claim 15 , wherein the instructions, when executed by the processor, further cause the apparatus to calculate the first sensor weight based on a probability density function (PDF).

20. The computer program product of claim 19 , wherein the instructions, when executed by the processor, further cause the apparatus to calculate the second sensor weight based on the PDF.

Assignees

• Univ Oklahoma

Inventors

• Mcdaniel Jay W
• Yeary Mark B
• Sigmarsson Hjalti H
• Sun Brian M

Classifications

• G01C21/165 Primary

  combined with non-inertial navigation instruments · CPC title

• G01S19/47 Primary

  the supplementary measurement being an inertial measurement, e.g. tightly coupled inertial · CPC title