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一种基于Unscented卡尔曼滤波的多平台多传感器配准算法
引用本文:胡洪涛,敬忠良,胡士强.一种基于Unscented卡尔曼滤波的多平台多传感器配准算法[J].上海交通大学学报,2005,39(9):1518-1521.
作者姓名:胡洪涛  敬忠良  胡士强
作者单位:上海交通大学,电子信息与电气工程学院,上海,200030
基金项目: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。

关 键 词:多平台多传感器  在线配准  Unscented卡尔曼滤波  状态估计
文章编号:1006-2467(2005)09-1518-04
收稿时间:2004-09-24
修稿时间:2004年9月24日

An Unscented Kalman Filter Based Multi-Platform Multi-Sensor Registration
HU Hong-tao,JING Zhong-liang,HU Shi-qiang.An Unscented Kalman Filter Based Multi-Platform Multi-Sensor Registration[J].Journal of Shanghai Jiaotong University,2005,39(9):1518-1521.
Authors:HU Hong-tao  JING Zhong-liang  HU Shi-qiang
Institution:School of Electronic, Information and Electrical Eng. , Shanghai Jiaotong Univ. , Shanghai 200030, China
Abstract: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.
Keywords:multi-platform multi-sensor  on-line registration  unscented Kalman filter(UKF)  state estimation
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