弹道目标微多普勒特性基于逆Radon变换的稀疏表示

作为识别空间弹道目标的有效方法,微多普勒特性提取对于雷达系统的时频分辨率提出了很高的要求,因此,要求雷达系统具有更高的采样频率。作为近年来新兴的技术手段,在远低于奈奎斯特采样定理的采样频率下,压缩感知技术可以对具有稀疏特性的信号实现高精度还原。对空间弹道目标时频分布进行逆Radon变换,在变换后的IRT域内获得时频分布的稀疏表示,从而可以借助压缩感知技术有效降低采样频率的要求。

Sparse Representation of Micro-Doppler Feature of Ballistic Target Based on Inverse Radon Transform

Micro -Doppler feature extraction, an effective method of space ballistic target recognition,requests for a higher time-frequency resolution,i.e. a higher sample frequency of radar system. Compressed sensing,an technology emerged recent years,could reconstruct original signal with sparse characteristic finely,from a sample which is obtained from sampling the original signal with a sampling frequency much lower than the Nyquist Sampling Theorem requested. The time-frequency distribution of space ballistic target will be applied inverse Radon transform in this article. The sparse representation in the IRT (Inverse Radon Transform) field is available to lower the requirement of sampling frequency with compressed sensing technology.