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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

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文摘 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。
其他语种文摘 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, explicit expressions for unbiased compensation coefficients 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. Results 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.
来源 机器人 ,2015,37(2):237-245,253 【核心库】
DOI 10.13973/j.cnki.robot.2015.0237
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
地址

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

语种 中文
文献类型 研究性论文
ISSN 1002-0446
学科 自动化技术、计算机技术
基金 国家自然科学基金资助项目 ;  基本科研业务费资助项目 ;  辽宁省自然科学基金 ;  中国科学院科技创新重点部署项目
文献收藏号 CSCD:5414403

参考文献 共 19 共1页

1.  Blackman S. Multiple target tracking with radar applications,1986 被引 8    
2.  Lerro D. Tracking with debiased consistent converted measurements versus EKF. IEEE Transactions on Aerospace and Electronic Systems,1993,29(3):1015-1022 被引 92    
3.  Mo L B. Unbiased converted measurements for tracking. IEEE Transactions on Aerospace and Electronic Systems,1998,34(3):1023-1027 被引 35    
4.  Duan Z S. Comments on "unbiased converted measurements for tracking". IEEE Transactions on Aerospace and Electronic Systems,2004,40(4):1374-1377 被引 30    
5.  Spitzmiller J N. Tracking with estimateconditioned debiased 3-D converted measurements. IEEE Aerospace Conference,2010:1-16 被引 1    
6.  Mei W. Unbiased Kalman filter using converted measurements: Revisit. Signal and Data Processing of Small Target,2009 被引 1    
7.  Bordonaro S V. Tracking with converted position and Doppler measurements. Signal and Data Processing of Small Target,2011 被引 1    
8.  王国宏. 均方意义下的最优无偏转换测量Kalman滤波. 系统仿真学报,2002,14(1):119-121 被引 6    
9.  Daum F E. Decoupled Kalman filters for phased array radar tracking. IEEE Transactions on Automatic Control,1983,28(3):269-283 被引 3    
10.  Baheti R S. Efficient approximation of Kalman filter for target tracking. IEEE Transactions on Aerospace and Electronic Systems,1986,22(1):8-14 被引 6    
11.  Sung T. A sufficient condition for stability of a decoupled tracking filter in LOS coordinate system. IEEE Transactions on Aerospace and Electronic Systems,1993,29(2):593-599 被引 2    
12.  Li X R. Canonical transform for tracking with Kinematic models. IEEE Transactions on Aerospace and Electronic Systems,1997,33(4):1212-1224 被引 6    
13.  伍明. 基于概率数据关联交互多模滤波的移动机器人未知环境下动态目标跟踪. 机器人,2012,34(6):668-679 被引 5    
14.  Miller M D. Coordinate transformation bias in target tracking. Signal and Data Processing of Small Target,1999:409-424 被引 1    
15.  Julier S J. A consistent, debiased method for converting between polar and Cartesian coordinate systems. Conference on Acquisition, Tracking, and Pointing XI,1997:110-121 被引 1    
16.  王宏强. 解耦的转换测量Kalman滤波算法. 电子学报,2003,31(6):867-870 被引 7    
17.  林晓君. 3维解耦转换量测Kalman滤波算法. 火控雷达技术,2005,34(3):6-12 被引 1    
18.  Blom H A P. The interacting multiple model algorithm for systems with Markovian switching coefficients. IEEE Transactions on Automatic Control,1988,33(8):780-783 被引 205    
19.  Yaakov B S. Estimation and tracking: Principles, techniques, and software,1993 被引 1    
引证文献 1

1 秦雷 临近空间目标非弹道式机动模式跟踪滤波技术 系统仿真学报,2017,29(6):1380-1385
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