National Key Laboratory of Radar Signal Processing, Xidian University, Xi'an 710071, China.
Air and Missile Defence College, Air Force Engineering University, Xi'an 710051, China.
Sensors (Basel). 2023 Jun 15;23(12):5619. doi: 10.3390/s23125619.
In the electronic warfare environment, the performance of ground-based radar target search is seriously degraded due to the existence of smeared spectrum (SMSP) jamming. SMSP jamming is generated by the self-defense jammer on the platform, playing an important role in electronic warfare, making traditional radars based on linear frequency modulation (LFM) waveforms face great challenges in searching for targets. To solve this problem, an SMSP mainlobe jamming suppression method based on a frequency diverse array (FDA) multiple-input multiple-output (MIMO) radar is proposed. The proposed method first uses the maximum entropy algorithm to estimate the target angle and eliminate the interference signals from the sidelobe. Then, the range-angle dependence of the FDA-MIMO radar signal is utilized, and the blind source separation (BSS) algorithm is used to separate the mainlobe interference signal and the target signal, avoiding the impact of mainlobe interference on target search. The simulation verifies that the target echo signal can be effectively separated, the similarity coefficient can reach more than 90% and the detection probability of the radar is significantly enhanced at a low signal-to-noise ratio.
在电子战环境中，由于存在展宽谱（SMSP）干扰，地面雷达目标搜索的性能严重下降。SMSP 干扰是由平台上的自卫干扰机产生的，在电子战中起着重要作用，使得基于线性调频（LFM）波形的传统雷达在搜索目标时面临巨大挑战。为了解决这个问题，提出了一种基于频率分集阵列（FDA）多输入多输出（MIMO）雷达的 SMSP 主瓣干扰抑制方法。该方法首先使用最大熵算法估计目标角度，并消除旁瓣干扰信号。然后，利用 FDA-MIMO 雷达信号的距离-角度相关性，使用盲源分离（BSS）算法分离主瓣干扰信号和目标信号，避免主瓣干扰对目标搜索的影响。仿真验证了目标回波信号可以有效分离，相似度系数可达 90%以上，雷达的检测概率在低信噪比下显著提高。
