摘要
通过对高速运动点目标的运动参量挖掘,实现对高速运动目标的速度、时延、方位等信号源参量的准确估计。传统方法主要采用宽带信号检测方法实现对高速运动点目标的参量挖掘和估计,当运动目标的时频特征具有窄带特性时,对目标运动参量估计精度不高。提出一种基于时频分析的高速运动点目标运动参量挖掘算法,构建高速运动点目标的信号回波模型,采用级联滤波算法对运动目标的干扰特征进行降噪滤波处理,对信号提取四阶累积量时频特征,直接获取近场源的参量,通过时频分析避免了谱峰搜索,减少对运动特征参量的挖掘计算量,提高参量估计精度。仿真结果表明,采用该算法进行高速运动点目标的运动参量挖掘和信号参量估计,能有效实现信号的抗干扰滤波,对运动目标的时延、方位角等参量估计精度较高,展示了较好的应用价值。
The accurate estimation for the speed,time delay and azimuth of high-speed moving target was realized by mining the motion parameters of the target. In view of the deficiency that traditional test method of broadband signal has low accuracy when time-frequency characteristics of the moving target has a narrow band feature,a new motion parameter mining method for high-speed moving point target based on time-frequency analysis is proposed. The echo signal model of high-speed moving point target was established. The denoise filtering processing for interference feature of moving target is carried out with cascade filtering algorithm. The fourth-order cumulant time-frequency characteristics of signals are extracted to obtain near-field source parameters directly,which avoided the spectrum peak search by time-frequency analysis,reduced the mining calculated quantity of motion characteristic parameters and improved the accuracy of parameter estimation. The simulation results show that the new method to excavate the moving target parameters and estimate the signal parameters can realize anti-interference filtering of signals effectively,and has high accuracy in parameter estimation of time-delay,azimuth,etc.
出处
《现代电子技术》
北大核心
2015年第20期31-34,37,共5页
Modern Electronics Technique
基金
江苏省产学研联合创新资金前瞻性联合研究项目:经编织造生产线智能物联技术开发与应用(BY2014042)
关键词
时频分析
运动目标
参量估计
数据挖掘
time frequency analysis
moving target
parameter estimation
data mining
