基于稀疏FrFT的窄带雷达目标架次识别方法

架次识别对于窄带雷达编队目标的探测与识别具有重要意义。本文基于最小熵准则提出了稀疏分数阶傅里叶变换(fractional Fourier transform, FrFT)最优变换阶次估计算法, 首先将雷达回波数据的FrFT结果的熵值建模为变换阶次的函数, 进而将变换阶次估计问题转化为稀疏优化问题, 利用稀疏重构算法获得最优变换阶次。最后，应用该算法分析窄带雷达多波门回波数据Doppler频率特性, 获取编队目标的架次信息。仿真和实测数据结果表明, 所提方法避免了暴力搜索能够快速获得FrFT最优变换阶次, 将该算法应用于窄带雷达回波信号处理能够准确识别编队目标架次信息。

Target sortie identification method of narrow-band radar based on sparse fractional Fourier transform

The sortie identification is of great significance for the detection and identification of narrow-band radar formation targets. Based on the minimum entropy criterion, an optimal transform order estimation algorithm of fractional Fourier transform (FrFT) is proposed in this paper. Firstly, the entropy of the FrFT result of radar echo data is modeled as a function of the transform order. Furthermore, the transformation order estimation problem is transformed into a sparse optimization problem, and the sparse reconstruction algorithm is used to obtain the optimal transformation order. Finally, the algorithm is applied to analyze the Doppler frequency characteristics of narrow-band radar multi-wave gate echo data, and obtain the sortie information of formation target. The results of simulation and measured data show that the proposed method avoids brute force search and can quickly obtain the optimal FrFT transform order. The algorithm can be used to accurately identify formation target sortie information when applied to narrow-band radar echo signal processing.