Efficient and Robust Automotive Radar Coherent Integration With Range Migration

Oded Bialer, A. Jonas, O. Longman
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Abstract

Conventional automotive radar perform range-Doppler coherent integration (stretch processing) under the assumption that the range of each object is constant during the integration interval. This assumption yields an efficient computation algorithm. However, when the object's relative speed is high and/or the coherent integration interval is large, the range migration is significant with respect to the range resolution, and as a result, the detection performance of the conventional range-Doppler coherent integration degrades significantly. The Radon-Fourier Transform (RFT) is the optimal method (in the sense of detection performance) for coherent integration with range migration, however, its complexity is large and may not be practical for implementation. In this paper, we develop a range-Doppler coherent integration algorithm that takes into account the range migration with efficient computation. We utilize the fact that range migration is a function of the Doppler frequency and derive an approximation to the RFT. The proposed algorithm significantly outperforms conventional coherent integration when the object's range migration is significant. Furthermore, it attains the performance of the RFT but with significantly lower complexity.
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基于距离偏移的高效鲁棒汽车雷达相干集成
传统的汽车雷达进行距离-多普勒相干积分(拉伸处理)时,假设在积分间隔内每个目标的距离是恒定的。这个假设产生了一种高效的计算算法。然而,当目标相对速度较大和/或相干积分间隔较大时,距离偏移对距离分辨率影响较大,导致常规距离-多普勒相干积分的检测性能明显下降。Radon-Fourier变换(RFT)是具有距离偏移的相干积分的最佳方法(从检测性能的意义上说),但其复杂性大,可能不太实用。本文提出了一种考虑距离偏移、计算效率高的距离-多普勒相干积分算法。我们利用距离偏移是多普勒频率的函数这一事实,推导出RFT的近似。当目标距离偏移较大时,该算法明显优于传统的相干积分算法。此外,它达到了RFT的性能,但显著降低了复杂度。
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