一种基于Unscented卡尔曼滤波的多平台多传感器配准算法  

An Unscented Kalman Filter Based Multi-Platform Multi-Sensor Registration

作　　者：胡洪涛[1] 敬忠良[1] 胡士强[1] 

机构地区：[1]上海交通大学电子信息与电气工程学院,上海200030

出　　处：《上海交通大学学报》2005年第9期1518-1521,共4页Journal of Shanghai Jiaotong University

基　　金：国家自然科学基金资助项目(60375008);国家科技攻关计划重点项目世博科技专项(2004BA908B07);高校博士点基金资助项目(20020248);航空科学基金资助项目(02D57003);上海市科技攻关重大预研项目(035115009)

摘　　要：首先给出传感器偏差配准模型,然后将目标的运动模型和传感器偏差组合在同一个状态方程中,利用Unscented卡尔曼滤波(UKF)方法进行状态和偏差联合估计,最后理论分析了配准偏差对状态估计的影响.Monte-Carlo仿真表明,该方法能同时有效地估计目标状态和传感器配准偏差.A registration model for misaligned sensors was given. The sensor misalignments and target states were incorporated into an augmented dynamic model, and an unscented Kalman filter （UKF） was proposed to estimate target states and register these sensors simultaneously. The effect of sensor misalignments upon the target states estimation was also analyzed theoretically. Simulations were used to demonstrate the effectiveness of the proposed algorithm.

关 键 词：多平台多传感器 在线配准 UNSCENTED卡尔曼滤波 状态估计 

分 类 号：TN953[电子电信—信号与信息处理]