Time-Frequency Analysis of Frequency Hopping Signals Based on Particle Swarm Optimization

被引：2
|
作者：
Guo Jiantao [1 ]
机构：
[1] Xinyang Normal Univ, Coll Phys & Elect Engn, Xinyang, Peoples R China
来源：
MECHANICAL ENGINEERING AND INTELLIGENT SYSTEMS, PTS 1 AND 2 | 2012年 / 195-196卷
关键词：
parameter estimationt; particle swarm optimization; frequency hopping signals;
D O I：
10.4028/www.scientific.net/AMM.195-196.265
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A new method is proposed for blind parameter estimation of frequency hopping signals. According to the relation between peaks location on the time frequency plane and component centers of frequency hopping signals, parameter estimation problem is solved using multi-species particle swarm optimization algorithm. Each particle moves around the time and frequency plan: and will converge to different species, which species seed represents the center of frequency hopping component. Using this method, the parameters of frequency hopping signals can be estimated. Simulation results demonstrate that the method is effective and feasible.
引用
收藏
页码：265 / 269
页数：5
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