基于切片熵权的WHT多LFM信号识别方法

发布时间：2019-06-29 19:31

【摘要】：为提高在低信噪比与先验信息不足条件下对线性调频(LFM)信号识别能力,借鉴信息论中的熵权法改进WHT(Wigner-Hough Transform),提出了一种基于切片熵权的WHTE(Wigner-Hough Transform based on Entropy)算法。推导出LFM信号的WHT与对应特性,将WHT变换域内极半径和角度切片的熵值来转换为权重因子,进而对每个切片进行加权处理,采用双层权重以弱化噪声与干扰项的影响,并推导出LFM信号与高斯白噪声在WHT维度内不同假设条件下的概率密度分布函数,构建了对于LFM信号WHT后恒虚警检测的完备流程。通过理论分析与公式推导论证了算法的可行性,并与WHT、分数阶傅里叶变换与周期WHT算法的仿真对比,验证了算法的有效性,凸显WHTE算法能够在强噪声背景下与没有先验支撑时实现对LFM信号的良好检测。
[Abstract]:In order to improve the recognition ability of LFM (LFM) signal under the condition of low SNR and insufficient prior information, a WHTE (Wigner-Hough Transform based on Entropy) algorithm based on slice entropy weight is proposed by using entropy weight method in information theory to improve WHT (Wigner-Hough Transform based on Entropy). The WHT and corresponding characteristics of LFM signal are derived, and the entropy value of pole radius and angle slice in WHT transform domain is converted into weight factor, and then each slice is weighted. Double-layer weight is used to weaken the influence of noise and interference term, and the probability density distribution function of LFM signal and Gaussian white noise under different assumptions in WHT dimension is derived, and a complete flow chart for CFAR detection of LFM signal after WHT is constructed. The feasibility of the algorithm is demonstrated by theoretical analysis and formula derivation, and compared with the simulation of WHT, fractional Fourier transform and periodic WHT algorithm, the effectiveness of the algorithm is verified, which highlights that the WHTE algorithm can detect the LFM signal well under the background of strong noise and without prior support.
【作者单位】：空军工程大学航空航天工程学院;西北工业大学电子与信息学院;
【基金】：航空科学基金(20152096019,20145596025)~~
【分类号】：TN911.7

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