基于先验知识的降维自适应时域滤波器

为了灵活调节时域滤波器各频率处能量以及利用先验知识提高机载雷达抑制杂波、干扰信号的性能,提出一种基于先验知识的降维自适应时域滤波器设计算法。首先结合先验知识估计机载雷达杂波协方差矩阵;然后通过这些信息,设计降维处理中时域滤波器各频率区域的增益;最后利用凸优化思想设计最优时域滤波器。结果表明:设计的时域滤波器通过分配不同区域的能量,保证在地杂波和干扰的多普勒区域处形成深宽凹口,不仅抑制了地杂波,还能够改善位于主杂波区域的压制性干扰,极大提高了机载雷达在复杂环境中检测目标的能力。

Research on Reduced-Dimensional Adaptive Time Domain Filter Based on Prior Knowledge

In order to flexibly adjust the energy at each frequency of the time domain filter and improve the performance of airborne radar to suppress clutter and interference signals by using prior knowledge, this paper proposes a time domain filter design algorithm based on prior knowledge of dimension reduction adaptive processing. Firstly the prior knowledge and conventional direction finding and ranging methods are combined to estimate the clutter power spectrum and the interference. Then, the information is used to design the gain of each frequency region of the dimension reduction processing. Finally, convex optimization idea design optimal time domain filter. The result show that the time domain filter designed in this paper distributes the energy of different regions to ensure the formation of deep and wide notches at the ground clutter and interference Doppler region, which not only suppresses ground clutter, but also improves the suppression in the main clutter region. These greatly improves the ability of airborne radar to detect targets in complex environments.