Fast Algorithm for Automotive Radar Target Detection in Mutual Interference

IF 0.3 Q4 ENGINEERING, ELECTRICAL & ELECTRONIC

IEICE Communications Express Pub Date : 2023-12-12 DOI:10.23919/comex.2023XBL0118

Ai Mingshun;Yang Weijie;Xu Li;Yan Guang;Yue Lingling;Yang Zijiang

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Abstract

As one of the important sensors for driving assistance, millimeter wave radar is of great significance for automotive safety driving. However, the problem of mutual interference between automotive radar signals is becoming a non negligible threat. Mutual interference can cause a significant performance decrease of radar target detection, and this artide proposes a simple and efficient target detection method to address this issue. The proposed method utilizes the distribution difference between target echoes and interference signals in the time-frequency domain to obtain a accumulation vector of spectral peaks, which follow a Poisson distribution. Based on that, the Poisson constant false alarm detection method is proposed to detect target echos effectively at low signal-to-interference ratios. The experimental results show that the detection accuracy of the method is above 95% when the signal-to-interference ratio is below -20dB. In addition, this algorithm does not require interference compression before detecting the target, and its computational complexity is only slightly greater than that of the short time Fourier transform, so it is a fast anti interference detection method.

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相互干扰中汽车雷达目标检测的快速算法

作为辅助驾驶的重要传感器之一，毫米波雷达对汽车安全驾驶具有重要意义。然而，汽车雷达信号之间的相互干扰问题正成为不可忽视的威胁。针对这一问题，本文提出了一种简单高效的目标检测方法。该方法利用目标回波与干扰信号在时频域上的分布差异，得到频谱峰值的累积向量，该向量服从泊松分布。在此基础上，提出了泊松常数误报检测方法，以在低信噪比情况下有效检测目标回声。实验结果表明，当信噪比低于 -20dB 时，该方法的检测准确率在 95% 以上。此外，该算法在检测目标之前不需要进行干扰压缩，其计算复杂度仅略高于短时傅里叶变换，是一种快速抗干扰检测方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEICE Communications Express ENGINEERING, ELECTRICAL & ELECTRONIC-

自引率

33.30%

发文量

114