Automatic Azimuth Alignment for Automotive Radar HUAYU Automotive Systems Company, Limited

Format:

Conference/Event

Author/Creator:

Guo, Guo, author.

Contributor:

Li, Kun

Sun, Shuangsuo

Conference Name:

Intelligent and Connected Vehicles Symposium (2018-08-14 : Kunshan City, Jiangsu, China)

Language:

English

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 2018

Summary:

AbstractThe world has witnessed the rapid development of the Advanced Driver Assist System (ADAS) industry over the past few years. Radar, as one of the most important sensors in ADAS due to its high penetration, all-weather characteristic and low cost, is studied intensively. Automobile radar has many applications like ACC (Advanced Cruise Control), BSD (Blind Spot Detection), LCA (Lane Change Assistant), et cetera, and the accuracy of the radar target detection influences the performance of ADAS. In general, range, velocity, azimuth angle and other target attributions are measured by the automotive radar, and the accuracy of the azimuth angle is more easily affected by the environment than other attributions. For the automotive radar, it is usually equipped either near a front bumper, or near a left rear and right rear bumper. Due to the small accidents which happened frequently and/or vibration in the course of vehicle driving, it will regularly lead to a misalignment azimuth angle, and will cause significant performance degradation of ADAS. To effectively solve this problem, a novel automatic azimuth alignment method for automotive radar is presented in this paper, compared with the traditional method, the guardrail is chose to do the misalignment angle estimation and a new fitting algorithm considering the characteristics of the data instead of the OLS (ordinary least squares) is implemented to calculate the misalignment angle, a comparison of different methods is carried out, and the validity and accuracy of the new method are shown by data measured on public road

Notes:

Vendor supplied data

Publisher Number:

2018-01-1606

Access Restriction:

Restricted for use by site license