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Gaussian Mixture Measurements for very long range tracking

机译：高斯混合测量，可进行远距离跟踪

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摘要

Target tracking with very long range is studied in this paper. Such tracking problem has severe measurement nonlinearity that will cause consistency problems and large tracking errors. Gaussian mixture measurements are obtained by dividing the measurement likelihood into several Gaussian components. The Gaussian Mixture Measurement-Integrated Track Splitting (GMM-ITS) is applied to very long range tracking scenarios. The simulation results show that the GMM-ITS can produce consistency in the filtering results crucial to the filter performance. Furthermore, it is also able to estimate the target state accurately with small tracking errors.
机译：本文研究了远距离目标跟踪。这种跟踪问题具有严重的测量非线性，这将导致一致性问题和较大的跟踪误差。高斯混合测量是通过将测量可能性分为几个高斯分量来获得的。高斯混合测量集成轨迹分割（GMM-ITS）适用于超长距离跟踪场景。仿真结果表明，GMM-ITS可以在对滤波器性能至关重要的滤波结果中产生一致性。此外，它还能够以很小的跟踪误差准确地估计目标状态。

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