Signal Modulation Characteristic Analysis Based on SFFT-Haar Algorithm
Weifeng Liu, Xiaochen Zhang · 2013
In the electromagnetic signal monitoring system, quality and quantity analysis are required to accurately and fast recognize the monitored signal and acquire modulated parameters. The algorithm that is based on the engineering is presented. It combines instant self-correlation algorithm (SFFT) and Haar wavelet transform to extract intra-pulse modulation feature. It was named SFFT-Haar. This paper first introduces the instant self-correlation algorithm and the wavelet transformation method respectively. Furthermore, the SFFT-Haar, an intrapulse modulation extraction method, is presented based on the above two approaches. Moreover, the intra-pulse modulation characteristics of four typical radar radiation source signals are analyzed. Finally, the simulation results illustrate this method. The algorithm has been applied in practice. (4 pages)