基于卡尔曼滤波的汽车雷达干扰抑制与信号恢复

Jaehoon Jung, Sohee Lim, Jinwook Kim, Seong-Cheol Kim, Seongwook Lee
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引用次数: 8

摘要

当一辆驶近的车辆上安装的雷达发送的信号与我们自己的雷达系统的频率重叠时,就会出现相互干扰的问题。当相互干扰发生时,目标信号被高功率的直接干扰信号所掩盖,降低了目标检测的性能。因此,我们提出了一种信号处理技术来恢复汽车雷达系统中因相互干扰而失真的信号,以提高目标检测的可靠性。首先,由于需要识别干扰发生的周期,提出了一种基于峰值检测的干扰周期查找方法。然后,利用卡尔曼滤波器将信号的未失真部分作为输入,恢复干扰区内的失真信号。在两个调频连续波雷达系统的仿真中,该方法有效地减轻了干扰的影响,准确地估计了目标信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Interference Suppression and Signal Restoration Using Kalman Filter in Automotive Radar Systems
When a radar equipped on an approaching vehicle transmits a signal whose frequency band overlaps with our own radar system, mutual interference problems arise. When mutual interference occurs, the target detection performance is degraded because the target signals are masked by the high power of direct interference signals. Therefore, we propose a signal processing technique to restore signals distorted by mutual interference in an automotive radar system to increase the reliability of target detection. First, since it is necessary to recognize the period where the interference occurred, a method to find the period of interference based on peak detection is presented. Then, the Kalman filter is employed to recover the distorted signal in the interference region by using the undistorted portion of the signal as its input. In simulations using two frequency modulated continuous wave radar systems, the influence of interference was effectively mitigated with our proposed method and target information was correctly estimated.
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