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An Application Research of Unbiased Converted Measurement Kalman Filter

机译:无偏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:无偏转换测量卡尔曼滤波器(UCMKF)保留了卡尔曼滤波器的优势,并已广泛用于目标跟踪。在实际应用中,发现当将UCMKF直接用于东-北-上坐标时,在某些运动模型或带有移动雷达的场景中,滤波器的性能会降低甚至出现差异。本文分析了这种情况下滤波器性能下降的原因,并将无偏转换测量卡尔曼滤波器(UCMKF)算法的应用扩展到以地球为中心的地球固定(ECEF)坐标来过滤随机误差。理论分析和仿真结果表明,该扩展算法与移动雷达具有更好的兼容性,在雷达高速移动时具有良好的滤波性能。

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