Meter-wave MIMO radar height measurement method based on adaptive beamforming

算法 计算机科学 波束赋形 雷达 多径传播 多输入多输出 干扰(通信) 频道(广播) 电信
作者
Chen Chen,Jianfeng Tao,Guimei Zheng,Yafei Song
出处
期刊:Digital Signal Processing [Elsevier BV]
卷期号:120: 103272-103272 被引量:7
标识
DOI:10.1016/j.dsp.2021.103272
摘要

Meter-wave MIMO radar has multipath effects in the low elevation angle area, seriously affecting the target elevation estimation performance. Therefore, the mainstream height measurement methods are generalized MUSIC and maximum likelihood estimation algorithms that do not require decoherence processing. Still, their complexity is high, and their performance is poor at low signal-to-noise ratios. Compressed sensing and time-reversal have been applied in height measurement, with good accuracy but high complexity. To quickly and accurately obtain the height parameters of the target, this paper proposes a low-elevation height measurement method for meter-wave MIMO radar based on adaptive beamforming. First, we analyze and simplify the signal model; then use the channel matching matrix to eliminate the influence of the reflected wave on the direct wave; then use the target direct wave direction and the reflected wave direction as the interference direction, and perform adaptive beamforming on it to obtain the target elevation angle value. Furthermore, the dimension reduction matrix is used to reduce the dimensionality of the received data signal. Then an algorithm suitable for undulating terrain and inclined ground is proposed and simulated. In addition, this paper gives the complexity of the proposed algorithm and the comparison algorithm. At last, in terms of the signal-to-noise ratio, the number of snapshots, the number of array elements, and the elevation angle, many simulation experiments are carried out to compare the proposed height measurement algorithm with the mainstream height measurement algorithm. The simulation results show that the accuracy and robustness of the proposed height measurement algorithm are the best under these factors.
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