CAJ | 학술논문

对雷达信号进行脉内特征分析，可以提高辐射源识别的准确率。通过信号的稀疏逼近，将LFM信号展开于一个超完备的冗余字典上，并利用DPT算法对字典进行改进。在压缩感知的理论基础上，先利用高斯随机矩阵进行压缩观测，再求解一个非线性优化问题，获得信号的调制参数。仿真结果表明，该方法具有传统稀疏分解法的估计性能，但运算量大大降低。
대뢰체신호진행맥내특정분석，가이제고복사원식별적준학솔。통과신호적희소핍근，장LFM신호전개우일개초완비적용여자전상，병이용DPT산법대자전진행개진。재압축감지적이론기출상，선이용고사수궤구진진행압축관측，재구해일개비선성우화문제，획득신호적조제삼수。방진결과표명，해방법구유전통희소분해법적고계성능，단운산량대대강저。
Intra-pulse feature analysis of radar signals can improve the accuracy rate of emitter identification. In this paper,the LFM signal is spread on a super-complete redundant dictionary through sparse decomposition.And then the method based on DPT algorithm is used to modify the sparse dictionary . The proposed method firstly compresses the signal with a random gauss matrix ,then reconstruct the original signal to get the modulation parameters by sloving a nonlinear problem based on Compressed Sensing(CS)theory. Simulations are presented to illustrate the performance of the method is comparable to the related sparse decomposition and its computation load is saved.