摘要
在多传感器多目标融合系统中,多传感器所提供的信息常常不同类,难以融合,建立多传感器多目标的随机集观测模型可以解决统一融合问题.基于随机集理论,根据虚警及漏测的情况,给出了目标的信任测度及其全局密度.从单传感器单目标推广到多传感器多目标,建立了实用的多目标随机集测量模型,并根据实例证明了该模型的实用性和有效性.
In a multi-sensor and multi-target fusion system, it is hard to fuse information collected by multi- sensor which is always in different data types. A random set measurement model to multi-target is a solution to uniform fusion. Based on random sets theory, false alarms and miss-detections in the background were considered, then, belief measure and its global density of targets were presented. From single-sensor single-target to multi-sensor multi-target, a useful random set measurement model to multi-target was proposed. The examples show that the proposed approach holds good effect and practicability on multi-target measurement.
出处
《上海交通大学学报》
EI
CAS
CSCD
北大核心
2007年第6期881-884,共4页
Journal of Shanghai Jiaotong University
基金
国防重点实验室预研基金资助项目(51476040103JW13)
关键词
多目标测量
随机集
杂波
信任测度
全局密度
multi-target measurement
random set
clutter
belief measure
global density
