Maneuvering Target Tracking in the Presence of Glint using the Nonlinear Gaussian Mixture Kalman Filter

Bilik I.; Tabrikian J.

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Maneuvering Target Tracking in the Presence of Glint using the Nonlinear Gaussian Mixture Kalman Filter

机译：使用非线性高斯混合卡尔曼滤波器在闪闪存在下的机动目标跟踪

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The problem of maneuvering target tracking in the presence of glint noise is addressed in this work. The main challenge in this problem stems from its nonlinearity and non-Gaussianity. A new estimator, named as nonlinear Gaussian mixture Kalman filter (NL-GMKF) is derived based on the minimum-mean-square error (MMSE) criterion and applied to the problem of maneuvering target tracking in the presence of glint. The tracking performance of the NL-GMKF is evaluated and compared with the interacting multiple modeling (IMM) implemented with extended Kalman filter (EKF), unscented Kalman filter (UKF), particle filter (PF) and the Gaussian sum PF (GSPF). It is shown that the NL-GMKF outperforms these algorithms in several examples with maneuvering target and/or glint noise measurements.

机译：这项工作解决了在存在闪烁噪声的情况下机动目标跟踪的问题。这个问题的主要挑战来自其非线性和非高斯性。基于最小均方误差（MMSE）准则，推导了一种新的估计器，称为非线性高斯混合卡尔曼滤波器（NL-GMKF），并将其应用于存在闪烁的机动目标跟踪问题。评估NL-GMKF的跟踪性能，并将其与使用扩展卡尔曼滤波器（EKF），无味卡尔曼滤波器（UKF），粒子滤波器（PF）和高斯和PF（GSPF）实施的交互多重建模（IMM）进行比较。结果表明，在一些示例中，NL-GMKF在操纵目标和/或闪烁噪声方面表现优于这些算法。

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《Aerospace and Electronic Systems, IEEE Transactions on》 |2010年第1期|P.246-262|共17页
作者
Bilik I.; Tabrikian J.;
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Dept. of Electr. & Comput. Eng., Univ. of Massachusetts, Dartmouth, MA, USA;

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机译：高斯混合减少在杂波中跟踪多个机动目标

Maneuvering Target Tracking in the Presence of Glint using the Nonlinear Gaussian Mixture Kalman Filter

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