稀疏傅里叶变换在雷达中的应用研究

Application research of sparse Fourier transform in radar

针对传统傅里叶变换计算量与所分析信号长度成正比,当采样率较大时,需要较大的运算时间问题,提出采用稀疏傅里叶变换(SFT)进行雷达信号处理,由于实际雷达目标多普勒频率个数有限,满足SFT方法使用条件,对SFT中的滤波器参数以及分段长度选择进行了分析与讨论,并给出了SFT处理雷达信号时的数学表达式;最后,利用仿真数据验证了该方法的性能,结果显示SFT在计算速度方面优于传统方法,可以提高目标信号参数的估计速度。

For a long time sequence radar signal, fast Fourier transform （FFT） needs large computation, In order to solve this problem,the paper proposes to use sparse Fourier transform （SFT） for radar signal processing, due to the actual radar target Doppler frequency numbers is limited , to meet the SFT method using conditions. In the paper, the SFT filter parameters and segment length selection are analyzed and discussed, and gives the SFT mathematical expression of the radar signal processingl Finally, the performance of the proposed method is validated with simulation data, the results show that the SFT is superior to the traditional methods in computational speed, and the estimated speed of the target signal parameters can be improved.