基于卡尔曼滤波的多目标宽带扩展函数估计  

Wideband Spread Function Estimation of Targets Based on Kalman Filtering Approach

作　　者：许杨文[1] 王万良[1] 

机构地区：[1]金华职业技术学院,浙江金华321017

出　　处：《计算机测量与控制》2010年第1期189-191,共3页Computer Measurement &Control

基　　金：教育部科学技术研究重点项目(106073)

摘　　要：针对在非平稳的声环境中,区分和定位多个运动目标的宽带反向散射问题,采用小波域宽带扩展函数方法对目标状态参量进行卡尔曼回归估计;基于小波变换的相关估计原理和宽带扩展函数,推导了使用Kailath的算法的回归扩展函数估计和校正的卡尔曼滤波器,讨论了适用于WTD-EC自适应模型的卡尔曼滤波器算法,使用宽带匹配滤波器产生的距离尺度映射,计算目标在时间延迟-时间尺度上的状态参量;最后通过数据仿真,研究了函数带宽和参数估计效果的关系,验证了算法在自适应检测及目标特征化方面的有效性。Based on Kalman filtering approach, state parameters of movement targets are estimated by wideband spread function estimation in wavelet transform domain. The regress spread function estimation and emendated Kalman filtering approach are deduced by Kailath algorithmic and wideband spread function, and the ability of the Kalman filter to track kinematics＇ properties of a multi-highlight scatter is studied. A wideband matching filter is used to acquire a scale-delay map which can be calculated to get the position of the target in time delaytime scale figure, and the algorithmic which is simulated in an example is validated available.

关 键 词：卡尔曼滤波 宽带扩展函数 多目标估计 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]