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An Application Research of Unbiased Converted Measurement Kalman Filter

机译:无偏见转换测量卡尔曼滤波器的应用研究

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摘要

The unbiased converted measurement Kalman filter (UCMKF) keeps the advantage of Kalman filter and has been widely used for target tracking. In the practical application, it is discovered that when the UCMKF is directly used in the east-north-up coordinates, the filter performance degrades or even diverges in some motion models or scenes with moving radars. In this paper, the cause of the degradation of filter performance in that situation is analyzed, and the application of unbiased converted measurement Kalman filter (UCMKF) algorithm is extended to Earth Centered Earth Fixed (ECEF) coordinate to filter random errors. Theoretical analyses and simulation results show that the extended algorithm is of better compatibility for moving radars, and owns a good filtering performance when the radar is moving with high-velocity.
机译:无偏见的转换测量卡尔曼滤波器(UCMKF)保持Kalman滤波器的优势,并且已广泛用于目标跟踪。在实际应用中,发现当UCMKF直接用于东北坐标时,滤波器性能下降甚至在具有移动雷达的某些运动模型或场景中发散。在本文中,分析了滤波器性能劣化的原因,并且不偏的转换测量卡尔曼滤波器(UCMKF)算法的应用延伸到地球中心固定(ECEF)坐标,以过滤随机误差。理论分析和仿真结果表明,当雷达以高速移动时,扩展算法对移动雷达具有更好的兼容性,并且在雷达移动时具有良好的过滤性能。

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