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Multiple target tracking with quantized measurements: A standard Bayesian approach

机译:具有量化测量的多目标跟踪:标准贝叶斯方法

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This paper shows how the use of standard Bayesian likelihood functions and particle filters provides a simple and general approach to tracking with quantized measurements. We demonstrate this result with two examples. The first involves a maneuvering target and the second multiple targets. In both cases the motion model for the target(s) is non-Gaussian and the quantized measurements correspond to a set of possible locations composed of disjoint regions in 2-space. For the multiple target example, we apply a nonlinear particle filter version of JPDA to perform the data association and tracking.
机译:本文说明了如何使用标准贝叶斯似然函数和粒子滤波器来提供一种简单而通用的跟踪量化测量的方法。我们用两个例子来证明这个结果。第一个涉及机动目标,第二个涉及多个目标。在两种情况下,目标的运动模型都是非高斯的,并且量化的测量值对应于一组可能的位置,这些位置由2空间中的不相交区域组成。对于多目标示例,我们应用了JPDA的非线性粒子滤波器版本来执行数据关联和跟踪。

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