Integrated positioning method and system

Patent metadata

Field	Value
Publication number	US-11073396-B2
Application number	US-201816179460-A
Country	US
Kind code	B2
Filing date	Nov 2, 2018
Priority date	Nov 15, 2017
Publication date	Jul 27, 2021
Grant date	Jul 27, 2021

Abstract

The present disclosure provides an integrated positioning method and system. The method comprises: receiving IMU data, and solving for the IMU data in a first Kalman filter to obtain a system state variable of an autonomous vehicle; receiving and buffering measurement data, and regarding the measurement data as current measurement data; performing measurement updating: obtaining the system state variable at a measurement time of current measurement data, and solving in the second Kalman filter to obtain an updated system state variable; if measurement data after the measurement time of the measurement data is already buffered, regarding the already-buffered measurement data after the measurement time as current measurement data, and performing the measurement update. The present disclosure can solve the problem about measurement information disorder caused by inconsistency of time delay in solving between different sensors, and improve real time and accuracy of the positioning.

First claim

What is claimed is:

1. A computer-implemented integrated positioning method for an autonomous vehicle, wherein the method comprises:
receiving IMU data of the autonomous vehicle, and solving using the IMU data in a first Kalman filter to obtain a system state variable of the autonomous vehicle;
receiving and buffering measurement data, and regarding the measurement data as current measurement data; performing measurement updating: obtaining the system state variable at a measurement time of current measurement data, and solving in a second Kalman filter to obtain an updated system state variable;
if measurement data after the measurement time of the measurement data is already buffered, regarding the already-buffered measurement data after the measurement time as current measurement data, and performing the measurement update for positioning the autonomous vehicle,
wherein said performing the measurement update comprises:
performing time update for the second Kalman filter until a measurement time of measurement data after the measurement time of the measurement data, and performing measurement update.

2. The computer-implemented method according to claim 1 , wherein the receiving IMU data, and solving using the IMU data in a first Kalman filter to obtain a system state variable of an autonomous vehicle comprises:
receiving the IMU data, and solving using the IMU data in the first Kalman filter to obtain a system state variable and an error state variable of the autonomous vehicle; storing in a buffer the IMU data and the system state variable of the autonomous vehicle obtained from the solving.

3. The computer-implemented method according to claim 2 , wherein the performing the measurement update comprises:
performing time update, assigning an error state variable in the first Kalman filter to the second Kalman filter, and obtaining, from the buffer of the first Kalman filter, the system state variable at the measurement time of the current measurement data;
performing measurement update, comprising: calculating an error state variable of the second Kalman filter to correct the system state variable, according to the current measurement data, and the system state variable and error state variable obtained by the first Kaman filter's solving.

4. The computer-implemented method according to claim 1 , wherein the performing time update for the second Kalman filter until a measurement time of measurement data after the measurement time of the measurement data, and performing measurement update further comprises:
if there are a plurality of measurement data, performing time update and measurement update for the second Kalman filter in turn, until a time of latest IMU data.

5. The computer-implemented method according to claim 1 , wherein after step of, if measurement data after the measurement time of the measurement data is already buffered, regarding the already-buffered measurement data after the measurement time as current measurement data, and performing the measurement update, the method further comprises:
performing time update for the second Kalman filter until a time of latest IMU data, and assigning the error state variable in the second Kalman filter to the first Kalman filter.

6. The computer-implemented method according to claim 1 , wherein the measurement data is GNSS or LiDAR measurement data.

7. A computer device, comprising a memory, a processor and a computer program which is stored on the memory and runnable on the processor, wherein the processor, upon executing the program, implements an integrated positioning method for an autonomous vehicle, wherein the method comprises:
receiving IMU data of the autonomous vehicle, and solving using the IMU data in a first Kalman filter to obtain a system state variable of the autonomous vehicle;
receiving and buffering measurement data, and regarding the measurement data as current measurement data; performing measurement updating: obtaining the system state variable at a measurement time of current measurement data, and solving in a second Kalman filter to obtain an updated system state variable;
if measurement data after the measurement time of the measurement data is already buffered, regarding the already-buffered measurement data after the measurement time as current measurement data, and performing the measurement update for positioning the autonomous vehicle,
wherein said performing the measurement update comprises:
performing time update for the second Kalman filter until a measurement time of measurement data after the measurement time of the measurement data, and performing measurement update.

8. The computer device according to claim 7 , wherein the receiving IMU data, and solving using the IMU data in a first Kalman filter to obtain a system state variable of an autonomous vehicle comprises:
receiving the IMU data, and solving using the IMU data in the first Kalman filter to obtain a system state variable and an error state variable of the autonomous vehicle; storing in a buffer the IMU data and the system state variable of the autonomous vehicle obtained from the solving.

9. The computer device according to claim 8 , wherein the performing the measurement update comprises:
performing time update, assigning an error state variable in the first Kalman filter to the second Kalman filter, and obtaining, from the buffer of the first Kalman filter, the system state variable at the measurement time of the current measurement data;
performing measurement update, comprising: calculating an error state variable of the second Kalman filter to correct the system state variable, according to the current measurement data, and the system state variable and error state variable obtained by the first Kaman filter's solving.

10. The computer device according to claimer 7 , wherein the performing time update for the second Kalman filter until a measurement time of measurement data after the measurement time of the measurement data, and performing measurement update further comprises:
if there are a plurality of measurement data, performing time update and measurement update for the second Kalman filter in turn, until a time of latest IMU data.

11. The computer device according to claim 7 , wherein after step of, if measurement data after the measurement time of the measurement data is already buffered, regarding the already-buffered measurement data after the measurement time as current measurement data, and performing the measurement update, the method further comprises:
performing time update for the second Kalman filter until a time of latest IMU data, and assigning the error state variable in the second Kalman filter to the first Kalman filter.

12. The computer device according to claim 7 , wherein the measurement data is GNSS or LiDAR measurement data.

13. A non-transitory computer-readable storage medium on which a computer program is stored, wherein the program, when executed by a processor, implements an integrated positioning method, wherein the method comprises:
receiving IMU data of the autonomous vehicle, and solving using the IMU data in a first Kalman filter to obtain a system state variable of the autonomous vehicle;
receiving and buffering measurement data, and regarding the measurement data as current measurement data; performing measurement updating: obtaining the system state variable at a measurement time of current measurement data, and solving in a second Kalman filter to obtain an updated system state variable;
if measurement data after the measurement time of the measurement data is already buffered, regarding the already-buffered measurement data after the measur

Assignees

• Baidu online network technology beijing co ltd

Inventors

• Yang Xiaolong
• Cai Renlan
• Song Shiyu
• Dong Fangfang

Classifications

• G01C21/005 Primary

  with correlation of navigation data from several sources, e.g. map or contour matching (G01C21/30 takes precedence) · CPC title

• G01C21/1652 Primary

  with ranging devices, e.g. LIDAR or RADAR · CPC title

• G01C21/20

  Instruments for performing navigational calculations (G01C21/24, G01C21/26 take precedence) · CPC title

• G01C21/165

  combined with non-inertial navigation instruments · CPC title