摘要
随着高级驾驶辅助系统的发展,毫米波雷达被广泛应用于汽车上,但随着道路上的雷达越来越多,雷达抗干扰也成为一个研究热点。线性调频连续波雷达之间的相互干扰可以分为交叉干扰和平行干扰,交叉干扰会使得本地噪声增加,降低目标的信噪比进而影响目标检测,平行干扰会产生虚假目标,但是出现的概率比较小。为了解决交叉干扰带来的影响,提出了自适应阈值和自回归模型相结合的方法,首先使用自适应阈值进行干扰检测,然后应用自回归模型恢复干扰点的采样值。仿真结果显示,上述方法在提高目标信噪比的同时也能够降低旁瓣的影响,并且在多干扰源情况下依然能够起到良好的干扰抑制效果。
With the development of Advanced Driver Assistance Systems, millimeter-wave radar is widely used in automobiles. But as more and more radars are on the road, radar interference has also become a research hotspot. The mutual interference between LFMCW radars can be divided into cross-interference and parallel interference. Cross interference will increase the noise floor, reduce the signal-to-noise ratio of the target and affect the target detection. Parallel interference will generate a ghost target in rare situations. In order to address the impact of cross-interference, we proposed a method of combining adaptive threshold and autoregressive model. First, an adaptive threshold was used to detect interference, and then an autoregressive model was used to restore the sampled value of the interference point. Simulation results show that this method can reduce the influence of side lobes while improving the target signal-to-noise ratio, and it can still play a good interference suppression effect in the case of multiple interference sources.
作者
蒋留兵
郑朋
车俐
JIANG Liu-bing;ZHENG Peng;CHE Li(School of Computer Science and Information Security,Guilin University of Electronic Technology,Guilin Guangxi 541004,China)
出处
《计算机仿真》
北大核心
2022年第6期135-140,174,共7页
Computer Simulation
基金
国家自然科学基金项目(61561010)
广西自然科学基金项目(2017GXNSFAA198089)
广西重点研发计划项目(桂科AB18126003,AB18221016)。
