混沌逆滤波与分形参数在目标检测中的应用  

Chaotic Inverse Filter and Fractal Parameter with Applications on Target Detection

作　　者：段晓君[1] 朱炬波[2] 

机构地区：[1]国防科技大学系统工程研究所,湖南长沙410073 [2]国防科技大学数学与系统科学系,湖南长沙410073

出　　处：《系统工程理论与实践》2002年第5期81-86,共6页Systems Engineering-Theory & Practice

基　　金：国家自然科学基金 ( 6 9872 0 39)

摘　　要：对目标跟踪的雷达测量数据进行处理 ,说明了通过混沌逆滤波可以找到观测数据中隐藏的工程背景中的动力特性 ;并且利用分形布朗运动 ( FBM)模型研究测量残差数据 ,其分形特性反映了目标的物理性质 .This paper provides methods to recover the dynamics and target characters from the measured data. An example of radar data proves that the dynamics hidden in observed data can be found by inverse filter of chaos. Using the Fractal Brownian Motion (FBM) model, we get fractal dimensions which show that fractal dimension of data from tracking vehicle by firing liquid is less than that by firing solid. It is also pointed out that chaotic inverse filter can be applied to increase the signal-to-noise ratio, and fractal dimension may be a new character index to identify targets in data processing on radar.

关 键 词：混沌 逆滤波 分形参数 目标检测 雷达 目标跟踪 

分 类 号：TN953[电子电信—信号与信息处理]