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本文介绍用于稠密目标环境的一种跟踪算法。该算法是为处理非常大量目标的被动式光学(仅有角度信息)敏感器而设计的。考虑到实际应用,敏感器的角度分辨力是有限的,采样率也极低。对于更复杂的算法设计问题,基本系统几乎是不可观察的。在这种情况下,标准的推广卡尔曼滤波器是不能用的;必须使用一种迭代式的最大似然估计器。
This article describes a tracking algorithm for dense target environments. The algorithm is designed to handle passive optical (angular only) sensors for a very large number of targets. Considering the practical application, the angle resolution of the sensor is limited, and the sampling rate is also very low. For more complex algorithm design problems, the basic system is almost unobservable. In this case, the standard extended Kalman filter can not be used; an iterative maximum likelihood estimator must be used.