面向目标跟踪的基于Rényi信息增量多的传感器管理  

Multi-sensor Management Based on Rényi Information Gain for Maneuvering Target-Tracking

作　　者：刘欣怡[1] 赵诚[1] 单甘霖[1] 王一川[1] 

机构地区：[1]军械工程学院电子与光学工程系,河北石家庄050003

出　　处：《信息与控制》2015年第2期184-189,共6页Information and Control

摘　　要：针对地面防空武器系统传感器的管理问题,面向机动目标跟踪,提出了一种基于Rényi信息增量的多传感器管理方案.首先利用交互式多模型容积卡尔曼滤波解决高斯非线性环境下系统状态估计问题,计算各目标和各传感器配对时的Rényi信息增量;然后建立了基于Rényi信息增量的多传感器管理模型,以系统总效能最大为原则选择传感器进行目标跟踪.关联仿真结果表明,该方法与基于Shannon信息增量的多传感器管理方法相比能够提高跟踪精度,实现传感器资源的有效利用.We propose a method for multi-sensor management,based on Rényi information gain,for tracking a ma-neuvering target.An interacting multiple model-cubature Kalman filter （IMM-CKF）algorithm is applied to obtain the maneuvering target′s location estimation and the Rényi information gain of each sensor for the Gaussian non-linear system.A multi-sensor management model is established to select sensors according to their maximal system effectiveness,based on the estimated location of the maneuvering target.The simulation results show that,when compare with the Shannon entropy-based method,our proposed method achieves grea-ter tracking accuracy and makes more effective use of sensor resources.

关 键 词：多传感器管理 机动目标跟踪 Rényi信息增量 容积卡尔曼滤波 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]