啁啾序列雷达相互干扰的慢时抑制

Máté Tóth, P. Meissner, A. Melzer, K. Witrisal
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引用次数: 3

摘要

汽车雷达越来越多地用于安全关键型高级驾驶辅助系统(ADAS)和自动驾驶应用。由于汽车频段的波形不稳定,配备雷达的车辆之间的相互干扰成为一个关键问题,因为它可能导致传感器性能的重大损失。本文介绍了一种新的啁啾序列雷达相互干扰模型和相应的抑制方法。该方法很好地集成到传统的距离-多普勒处理链中,并能够控制干扰抑制和信号失真之间的固有权衡。在统计性能分析框架内使用广泛的模拟来讨论其特性。在研究的场景中,该方法在不引入假警报的情况下提高了检测性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Slow-Time Mitigation of Mutual Interference in Chirp Sequence Radar
Automotive radars are increasingly used for safety-critical advanced driver assistance systems (ADAS) and autonomous driving applications. Due to unregulated waveforms in the automotive frequency bands, mutual interference between radar-equipped vehicles is becoming a key issue, as it can lead to significant losses of sensor performance. In this work, a novel mutual interference model and a subsequent mitigation method are introduced for chirp sequence radars. The method integrates well into the conventional range-Doppler processing chain, and enables control over the inherent trade-off between interference suppression and signal distortion. Its properties are discussed using extensive simulations within a statistical performance analysis framework. In the investigated scenarios, the method achieved an improvement in detection performance without introducing false alarms.
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