标题:
基于小波变换的多分辨率分析分割算法的研究The Multi-Resolution Analysis Segmentation Research
Based on Wavelet
作者:
费洪亮
关键字:
跳频信号, 特征提取, 小波脊线Frequency Hopping Signals; Feature Extraction; Wavelet Ridge
期刊名称:
《Hans Journal of Data Mining》, Vol.2 No.2, 2012-04-05
摘要:
跳频信号以其自身优良的抗截获、抗干扰能力，在军事通信中得到了广泛的应用，因此，对跳频信号的截获展开研究具有非常重要的现实意义。本文采用时频联合分析的方法，深入研究了跳频信号在线自动盲检测和频点搜索捕获问题，并对其特征参数提取算法进行了研究。针对跳频信号的特征提取，研究了一种基于小波脊线的特征提取算法，通过matlab仿真实验对方法的性能进行了验证，实验表明基于小波脊线的特征提取算法有很大的性能优势，进一步提高了频率估计的准确性和时效。
Frequency hopping signals in their own excellent anti-interception, anti-interference ability, in the military communication has been widely applied, therefore, it has a very important practical significance for the research of interceptting the frequency hopping signals. In this paper, the joint time-frequency analysis, in-depth study of the frequency hopping signal line automatic detection and frequency blind search acquisition issues, and its feature extraction algorithm is studied. Frequency hopping signals for feature extraction of a feature based on wavelet ridge extraction algorithm, the matlab simulation results the performance of the method was validated by experimental results show that the characteristics of wavelet ridge extraction algorithm is very performance advantages, and further improve the frequency estimation accuracy and timeliness.