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Empirical evidence of bias in extended Kalman filters used for passive target tracking

机译:用于被动目标跟踪的扩展卡尔曼滤波器中的偏差的经验证据

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The bearings-only estimation problem and its application to the intercept of an aircraft target by an air-to-air missile are discussed. That is, how does one estimate the state of a system of a missile and a target (relative position, relative velocity, and target acceleration) in a plane with measurements of the line-of-sight (LOS) or bearing angle only? The ownship-to-target range is unobservable unless the LOS rate is nonzero. The range and range-rate estimates are biased for both the extended Kalman filter (EKF) and the modified gain EKF (MGEKF). Empirical evidence of this biasing is presented using a simple simulation. The bias is shown to be caused by a correlation between the gain and innovations sequences. It is further shown that this bias is not removed (though it is reduced and bounded) when the range is observable.
机译:讨论了纯方位估计问题及其在空空导弹拦截飞机目标中的应用。也就是说,如何仅通过视线(LOS)或方位角的测量来估计平面上的导弹和目标系统(相对位置,相对速度和目标加速度)的状态?除非LOS率不为零,否则从目标到目标的所有权范围是不可观察的。扩展卡尔曼滤波器(EKF)和修正增益EKF(MGEKF)都对范围和范围速率估计值有偏见。使用简单的模拟就可以得出这种偏见的经验证据。偏差被证明是由增益和创新序列之间的相关性引起的。进一步表明,当该范围可观察到时,该偏差不会消除(尽管会减小和限制)。

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