基于最小二乘法的脉冲压缩技术研究

Research on Pulse Compression Technology Based on Least Square Method

线性调频信号(LFM)是一种常用的脉冲压缩信号,其脉冲压缩通常会带来较高的距离旁瓣,进行加权的旁瓣抑制方法后,不仅没有很好的主副瓣比而且会导致主瓣展宽,其性能不能满足实际应用要求。最小二乘算法通过最小误差的平方和寻找最佳函数匹配,可以求得数据与期望数据之间的误差的平方和最小。通过迭代最小二乘法对脉冲压缩后的输出进行优化,以获得更好的主副瓣之比和更窄的主瓣宽度,通过仿真实验表明,基于最小二乘法的脉冲压缩算法有比较好的旁瓣抑制能力和距离分辨率。

The LFM signal is a commonly used pulse compression signal and its pulse compression usually leads to a higher distance side-lobe. The weighted side-lobe suppression method not only no good peak side-lobe ratio and can lead to the main lobe broadening,so its performance cannot meet the practical application requirements. The least squares algorithm based on minimum error square and find the best matching function,and the minimum error can be obtained between the data and the expected data. The pulse-compressed output is optimized by an iterative least squares method to achieve better peak side-lobe ratio and narrower main lobe width. The simulation results show that the method of least squares based on pulse compression algorithms have a better side lobe suppression capability and range resolution.