Cascaded Kalman filter for target tracking in automotive radar

被引:5
作者
Li, Yang [1 ,2 ]
Liang, Can [1 ,2 ]
Lu, Man [3 ]
Hu, Xueyao [1 ,2 ]
Wang, Yanhua [1 ,2 ]
机构
[1] Beijing Inst Technol, Sch Informat & Elect, Radar Res Lab, Beijing, Peoples R China
[2] Beijing Key Lab Embedded Real Time Informat Proc, Beijing, Peoples R China
[3] Beijing Racobit Elect Informat Technol Co Ltd, Beijing, Peoples R China
来源
JOURNAL OF ENGINEERING-JOE | 2019年 / 2019卷 / 19期
基金
中国国家自然科学基金;
关键词
Doppler radar; measurement errors; road vehicle radar; Kalman filters; FM radar; CW radar; target tracking; frequency modulation; radar signal processing; automotive radar; automotive anti-collision radar system; key indicators; radar performance; frequency modulation continuous wave radar; chirp sequence; velocity ambiguity; measurement error; cascaded Kalman filter algorithm; staggered pulse repetition frequency signal; multiple pulse repetition frequency signal; tracking performance; COLLISION-AVOIDANCE;
D O I
10.1049/joe.2019.0159
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In automotive anti-collision radar system, the accuracy of velocity is one of the key indicators to measure radar performance. For frequency modulation continuous wave radar with chirp sequence, which is commonly used in automotive radar, there are two problems that are velocity ambiguity and measurement error. In order to address these problems, a cascaded Kalman filter algorithm is proposed in this article, which is able to overcome velocity ambiguity and improve the accuracy of measurements. In addition, the problem of velocity ambiguity can be solved just in the data processing and it avoids transmitting staggered or multiple pulse repetition frequency signal. The simulation results show that this algorithm can effectively improve the tracking performance.
引用
收藏
页码:6264 / 6267
页数:4
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