Method of determination of alignment angles of radar sensors for a road vehicle radar auto-alignment controller
Gespeichert in:
| Titel: | Method of determination of alignment angles of radar sensors for a road vehicle radar auto-alignment controller |
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| Patent Number: | 11899,100 |
| Publikationsdatum: | February 13, 2024 |
| Appl. No: | 16/905379 |
| Application Filed: | June 18, 2020 |
| Abstract: | A method of determination of the alignment angles of two or more road vehicle (1) borne radar sensors (4) for a road vehicle radar auto-alignment controller (3) starting from initially available rough estimates of alignment angles. From at least two radar sensors (4) are obtained signals related to range, azimuth and range rate to detections. The detections are screened (5) to determine detections from stationary targets. From the determined detections from stationary targets is derived a linearized signal processing model involving alignment angles, longitudinal and lateral velocity and yaw-rate of the road vehicle (1). A filter algorithm is applied to estimate the alignment angles. Based on the estimated alignment angles are produced signals suitable for causing a road vehicle (1) radar auto-alignment controller (3) to perform radar offset compensation. |
| Inventors: | Zenuity AB (Gothenburg, SE) |
| Assignees: | Zenuity AB (Gothenburg, SE) |
| Claim: | 1. A method of determining alignment angles of at least two or more road vehicle borne radar sensors for producing signals suitable to cause a road vehicle radar auto-alignment controller to perform radar offset compensation starting from initially available rough estimates of the alignment angles, the method comprising: obtaining, from the at least two or more road vehicle borne radar sensors, signals related to range, azimuth, and range rate to detections; screening the obtained signals from the at least two or more road vehicle borne radar sensors to determine detections from stationary targets; deriving, from the determined detections from stationary targets based on the obtained signals from the at least two or more road vehicles borne radar sensors, a linearized signal processing model involving the alignment angles, longitudinal and lateral velocity, and yaw-rate of the road vehicle, the linearized signal processing model linearized with respect to alignment angles having the initially available rough estimates of the alignment angles; applying a Kalman filter algorithm to the linearized signal processing model to estimate the alignment angles for the at least two or more road vehicle borne radar sensors by combining the obtained signals from all of the at least two or more road vehicle borne radar sensors; producing, based on the estimated alignment angles, the signals suitable to cause the road vehicle radar auto-alignment controller to perform the radar offset compensation. |
| Claim: | 2. The method according to claim 1 , further comprising obtaining the initially available rough estimates of the alignment angles from known nominal mounting angles of the at least two or more road vehicle borne radar sensors. |
| Claim: | 3. The method according to claim 1 , wherein the screening the detections to determine detections from stationary targets is done through monitoring longitudinal and lateral velocity and yaw-rate of the road vehicle together with the obtained range-rates of the detections. |
| Claim: | 4. The method according to claim 1 , wherein the screening the detections to determine detections from stationary targets is done using Random Sample Consensus (RANSAC) techniques or by running target tracking and looking at temporal effects. |
| Claim: | 5. The method according to claim 1 , wherein the deriving the linearized signal processing model is done by performing a Taylor series expansion of a rotation matrix involving the alignment angles. |
| Claim: | 6. A road vehicle system comprising a road vehicle radar auto-alignment controller that performs the radar offset compensation based on the signals produced in accordance with the method of claim 1 . |
| Claim: | 7. A road vehicle comprising a road vehicle system comprising a road vehicle radar auto-alignment controller that performs the radar offset compensation based on the signals produced in accordance with the method of claim 1 . |
| Claim: | 8. A computer program embodied on a non-transitory computer-readable storage medium, the computer program comprising program code for controlling a road vehicle radar auto-alignment controller to execute a process for road vehicle radar auto-alignment, the process comprising the method of claim 1 . |
| Claim: | 9. A computer program embodied on a non-transitory computer-readable storage medium, the computer program comprising instructions that when executed by a processing circuit is configured to cause the road vehicle system to perform the method according to claim 1 . |
| Claim: | 10. A method of determining alignment angles of at least two or more road vehicle borne radar sensors for producing signals suitable to cause a road vehicle radar auto-alignment controller to perform radar offset compensation starting from initially available rough estimates of the alignment angles, the method comprising: obtaining, from the at least two or more road vehicle borne radar sensors, signals related to range, azimuth, and range rate to detections; screening the obtained signals from the at least two or more road vehicle borne radar sensors to determine detections from stationary targets; deriving, from the determined detections from stationary targets based on the obtained signals from the at least two or more road vehicles borne radar sensors, a linearized signal processing model involving the alignment angles, longitudinal and lateral velocity, and yaw-rate of the road vehicle, the linearized signal processing model linearized with respect to alignment angles having the initially available rough estimates of the alignment angles; estimating the alignment angles for the at least two or more road vehicle borne radar sensors by applying a Kalman filter algorithm to the linearized signal processing model by combining the obtained signals from all of the at least two or more road vehicle borne radar sensors; and performing the radar offset compensation, based on the estimated alignment angles, by the road vehicle radar auto-alignment controller. |
| Claim: | 11. The method of claim 10 , wherein the radar offset compensation is a difference between the initially available rough estimates of the alignment angles and the estimated alignment angles. |
| Claim: | 12. A method of performing radar offset compensation of at least two or more road vehicle borne radar sensors, the method comprising: obtaining, from the at least two or more road vehicle borne radar sensors, signals related to range, azimuth, and range rate to detections; screening the obtained signals from the at least two or more road vehicle borne radar sensors to determine detections from stationary targets; deriving, from the determined detections from stationary targets based on the obtained signals from the at least two or more road vehicles borne radar sensors, a linearized signal processing model involving alignment angles, longitudinal and lateral velocity, and yaw-rate of the road vehicle, the linearized signal processing model linearized with respect to initially available rough estimates of the alignment angles; estimating the alignment angles for the at least two or more road vehicle borne radar sensors by applying a Kalman filter algorithm to the linearized signal processing model by combining the obtained signals from all of the at least two or more road vehicle borne radar sensors; and causing a road vehicle radar auto-alignment controller to perform the radar offset compensation of two or more road vehicle borne radar sensors based on the estimated alignment angles. |
| Patent References Cited: | 5964822 October 1999 Alland 6763318 July 2004 Winter 7337650 March 2008 Preston 7991550 August 2011 Zeng 8775064 July 2014 Zeng 9618616 April 2017 Kishigami 9776629 October 2017 Heinrichs-Bartscher 10088553 October 2018 Zeng 10202125 February 2019 Kasaiezadeh Mahabadi 10634777 April 2020 Oh 10816344 October 2020 Schiffmann 20080300787 December 2008 Zeng 20120022739 January 2012 Zeng 20120290169 November 2012 Zeng 20150247924 September 2015 Kishigami 20150276923 October 2015 Song et al. 20160223661 August 2016 Song et al. 20170261599 September 2017 Zeng 20180297605 October 2018 Kasaiezadeh Mahabadi 20190187250 June 2019 Ru 20190277639 September 2019 Schiffmann 20190369222 December 2019 Oh 20210124041 April 2021 Proefrock 20220317288 October 2022 Goda 2068173 June 2009 3279683 July 2018 |
| Other References: | Kellner et al., “Joint Radar Alignment and Odometry Calibration”, 18th International Conference on Information Fusion, Jul. 6-9, 2015, pp. 366-374. cited by applicant Kellner et al., “Instanteous Ego-Motion Estimation using Multiple Doppler Radars”, IEEE, 2014, May 31-Jun. 7, 2014, pp. 1592-1597. cited by applicant |
| Assistant Examiner: | Justice, Michael W |
| Primary Examiner: | Magloire, Vladimir |
| Attorney, Agent or Firm: | DUANE MORRIS LLP Lefkowitz, Gregory M. Pyles, Randall C. |
| Dokumentencode: | edspgr.11899100 |
| Datenbank: | USPTO Patent Grants |
| Abstract: | A method of determination of the alignment angles of two or more road vehicle (1) borne radar sensors (4) for a road vehicle radar auto-alignment controller (3) starting from initially available rough estimates of alignment angles. From at least two radar sensors (4) are obtained signals related to range, azimuth and range rate to detections. The detections are screened (5) to determine detections from stationary targets. From the determined detections from stationary targets is derived a linearized signal processing model involving alignment angles, longitudinal and lateral velocity and yaw-rate of the road vehicle (1). A filter algorithm is applied to estimate the alignment angles. Based on the estimated alignment angles are produced signals suitable for causing a road vehicle (1) radar auto-alignment controller (3) to perform radar offset compensation. |
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