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基于卡尔曼滤波预测的无偏量测转换方法
Tracking with prediction-conditioned unbiased converted measurements

查看参考文献14篇

文摘 针对在目标跟踪系统中通常使用量测转换方法将球面坐标系下的量测量转换到笛卡尔坐标系下,传统量测转换方法在互距离测量误差增大时跟踪性能有所下降的问题,提出一种基于卡尔曼滤波预测的无偏量测转换方法。采用无偏量测转换方法变换量测量,基于卡尔曼滤波预测值,结合无迹变换算法估计转换量测方差。仿真结果表明,所提出的转换量测卡尔曼滤波算法较现有方法具有更高的跟踪精度和可信度。
其他语种文摘 In target tracking system, the converted measurement method is usually used to convert spherical measurements to a Cartesian frame of reference. The performance of the conventional converted measurement degrades for large cross-range errors. A prediction-conditioned unbiased conversion is presented. The unbiased conversion is used and the covariance of the converted measurements is approximated by the Kalman prediction and unscented transform. Simulation results show that the converted measurement Kalman filter proposed is more accurate and credible.
来源 控制与决策 ,2015,30(2):229-234 【核心库】
DOI 10.13195/j.kzyjc.2014.0041
关键词 目标跟踪 ; 量测转换 ; 方差估计 ; 无迹变换 ; 卡尔曼滤波
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, 沈阳, 110016

语种 中文
文献类型 研究性论文
ISSN 1001-0920
学科 自动化技术、计算机技术
基金 中国科学院科技创新重点部署项目 ;  基础科研项目 ;  国家自然科学基金项目 ;  辽宁省自然科学基金
文献收藏号 CSCD:5371016

参考文献 共 14 共1页

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