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Adaptive filtering and imaging algorithms for tracking maneuvering targets

机译:用于跟踪机动目标的自适应滤波和成像算法

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Evasive target maneuvers create problems for traditional tracking algorithms because maneuver accelerations are frequently abrupt and not adequately modeled by wideband noise processes. Earlier work has suggested the use of an imaging sensor to determine target orientation, from which the likely direction of a maneuver acceleration can be inferred. The authors compare this strategy with other, more traditional approaches in the context of tracking a maneuvering target in the plane. The augmented measurement filter, EKFp (extended Kalman filter-p), achieved excellent performance results in both nominal operation and in operation during the maneuver, indicating the superiority of the image augmented filtering system. This superiority in performance comes at the cost of additional hardware and a more complicated filter, but these indicate that this augmented measurement filter is a fruitful area of inquiry.
机译:逃避的目标机动为传统的跟踪算法带来了问题,因为机动加速经常会突然发生,并且无法通过宽带噪声过程进行充分建模。较早的工作建议使用成像传感器来确定目标方向,从中可以推断出可能的机动加速方向。作者在跟踪飞机上的机动目标的情况下,将该策略与其他更传统的方法进行了比较。增强测量滤波器EKFp(扩展卡尔曼滤波器-p)在标称运行和操纵过程中均获得了出色的性能结果,表明图像增强滤波系统的优越性。性能上的优越性是以附加硬件和更复杂的滤波器为代价的,但是这些表明,这种增强的测量滤波器是一个富有成果的研究领域。

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