多目标雷达组网实时系统偏差稳健估计研究  

Real-Time Robust Estimation of Sensor Bias for Radar Network under Multi-Target Circumstance

作　　者：张宇[1] 王国宏[1] 陈垒[1] 张磊[1] 

机构地区：[1]海军航空工程学院信息融合技术研究所,山东烟台264001

出　　处：《电光与控制》2013年第2期5-7,27,共4页Electronics Optics & Control

基　　金：国家自然科学基金项目(61032001;60972159;61002006);航空科学基金(20085184003);"泰山学者"建设工程专项经费资助项目

摘　　要：针对多目标情况下雷达组网的误差配准问题,提出了一种基于Kalman滤波和数据融合的系统偏差实时稳健估计方法。首先,利用Kalman滤波的实时配准算法得到各个目标对雷达系统偏差的估计结果;然后,通过估计结果的实时融合进一步减小估计误差;最终得到较高精度的实时系统偏差估计。仿真结果表明,该算法可以有效地实现多目标情况下的实时误差配准。A novel real-time robust estimation method based on Kalman filter and data fusion was proposed for error estimation of radar network under multi-target circumstance. Firstly, the real-time registration algorithm of Kalman filter was utilized to get the estimated system bias by each target. Then, the results were processed by real-time data fusion to make the estimated bias more precise. Simulation results show that real-time error registration under multi-target circumstance can be realized more effectively.

关 键 词：雷达组网 误差配准 卡尔曼滤波 实时类算法 数据融合 

分 类 号：V271.4[航空宇航科学与技术—飞行器设计] TN957[电子电信—信号与信息处理]