火力与指挥控制Issue(4)：6-9,4.
基于时变量测方差的多传感器多目标优化分配算法
Sensor Assignment Method Based on Time-varying Measurement Variance for Tracking Multi-targets
摘要
Abstract
The target states are usually in Cartesian coordinates while the measurement values are in polar coordinates in target tracking system. The measurement variance is usually assumed fixed,which may lead to filter divergence in the algorithm based on kalman filter and its extension. Hence,an optimal sensor assignment method based on time varying measurement variance for tracking multi-targets is presented. It gets the time-varying measurement variance by converted measuring coordinates and estimates the covariance with the converted measurement kalman filtering algorithm. The sensor assignment for tracking multi-target can be implemented with the cost function of the covariance. Finally,the simulation shows that the algorithm can meet the tracking accuracy requirements while utilize the sensor resources fully.关键词
目标跟踪/测量方差/传感器管理/多传感器多目标分配/转化卡尔曼滤波算法Key words
target tracking/measurement variance/sensor management/assignment of multi-sensors for tracking multi-targets/converted measurement kalman filtering分类
信息技术与安全科学引用本文复制引用
方余瑜,左燕,谷雨,薛安克..基于时变量测方差的多传感器多目标优化分配算法[J].火力与指挥控制,2015,(4):6-9,4.基金项目
国家自然科学基金（61004119，61174024）；国家“九七三”计划基金资助项目 （）
