船舶静态电场跟踪的渐进更新扩展卡尔曼滤波器  

A progressive update extended Kalman filter for ship tracking with static electric field

作　　者：孙宝全[1] 颜冰[1] 姜润翔[1] 张伽伟[1] SUN Baoquan;YAN Bing;JIANG Runxiang;ZHANG Jiawei(College of Weapon Engineering,Naval University of Engineering,Wuhan 430033,China)

机构地区：[1]海军工程大学兵器工程学院,湖北武汉430033

出　　处：《国防科技大学学报》2018年第6期134-140,共7页Journal of National University of Defense Technology

基　　金：国家自然科学基金青年科学基金资助项目(51509252);国家自然科学基金资助项目(41476154)

摘　　要：为了实现利用船舶静态电场对船舶进行跟踪的目的,针对传统卡尔曼滤波算法中存在的问题,设计一种新的非线性滤波器。建立船舶的状态空间模型,分析传统卡尔曼滤波算法在船舶跟踪中存在的问题;依据渐进贝叶斯思想,利用连续白噪声与离散白噪声序列噪声协方差之间的关系,设计一种新的渐进更新扩展卡尔曼滤波器。仿真结果表明,该滤波器能有效地抑制由于初始误差较大而造成的滤波性能下降和滤波发散,能够有效地跟踪船舶,具有较高的实用价值。In order to track the ship with static electric field,aiming at the problem of traditional Kalman filters,a new nonlinear filter was designed. Ship state space model was established,and the problem of traditional Kalman filtering algorithm in ship tracking was analyzed;according to the relationship of noise covariance between the continuous white noise and discrete white noise sequence,a new progressive update extended Kalman filter was proposed on progressive Bayes theory. Simulation results show that the new method can effectively reduce the filtering performance degradation and filtering divergence caused by large initial error,thus can effectively be used to track the ship,and has high practical value.

关 键 词：非线性滤波器 船舶静态电场 状态空间模型 扩展卡尔曼滤波器 

分 类 号：TJ610[兵器科学与技术—武器系统与运用工程]