基于修正加权矩阵的3维解耦无偏量测转换交互式多模型算法  

A Decoupled Interacting Multiple Model Algorithm with Unbiased 3D Converted Measurements Based on Modified Weighted Matrix

作　　者：李为[1,2] 李一平[1,2] 封锡盛[1] 

机构地区：[1]中国科学院沈阳自动化研究所机器人学国家重点实验室,辽宁沈阳110016 [2]中国科学院大学,北京100049

出　　处：《机器人》2015年第2期237-245,253,共10页Robot

基　　金：中国科学院科技创新重点部署项目(KGFZD-125-014);基本科研业务费资助项目(B1320133015);国家自然科学基金资助项目(61273334);辽宁省自然科学基金资助项目(2011010025-401)

摘　　要：为解决使用正规变换方法解耦高维耦合运动模型进行机动目标跟踪造成各坐标轴估计结果相互影响的问题,提出了一种改进的解耦方法.首先给出了基于卡尔曼滤波预测量的3维无偏量测补偿系数和转换量测方差表达式.然后在正规变换的基础上,详细给出了构造修正加权矩阵的改进解耦方法.最后结合交互式多模型算法进行了仿真实验,结果表明该方法能够在减少计算量的同时,消除各坐标轴向估计结果之间的相互影响,有利于交互式多模型算法的分析和使用.In order to solve the problem of mutual influence among the estimations of each coordinate caused by the canonical transform used for decoupling high-dimensional coupled kinematic state models in maneuvering targets tracking applications, an improved decoupling method is presented. At first, expJicit expressions for unbiased compensation coeffi- cients and unbiased covariance statistics based on Kalman filter predictions related to the 3D measurements are given. And then, based on the canonical transform, an improved decoupling method using the modified weighted matrix is presented in detail. At last, simulation experiments are conducted combining with the IMM （interacting multiple model） algorithm. Re- suits indicate that the proposed algorithm can reduce computational burden and eliminate influences among three Cartesian coordinates, which is good for analysis and application of IMM algorithm.

关 键 词：量测转换 卡尔曼滤波预测量 交互式多模型算法 正规变换 解耦 

分 类 号：TP212[自动化与计算机技术—检测技术与自动化装置]