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Multiple target tracking with quantized measurements: A standard Bayesian approach

机译:具有量化测量的多个目标跟踪: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:本文展示了如何使用标准贝叶斯似函数和粒子滤波器提供了一种用量化测量跟踪的简单和一般的方法。我们用两个例子演示了这一结果。第一个涉及机动目标和第二多个目标。在这两种情况下,目标的运动模型是非高斯,并且量化测量对应于由2空间中的不相交区域组成的一组可能的位置。对于多个目标示例,我们应用JPDA的非线性粒子滤波器版本以执行数据关联和跟踪。

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