Piecewise optimal trajectories of observer for bearings-only tracking by quantization

Huilong Zhang, F. Dufour, Jonatha Anselmi, D. Laneuville, A. Negre
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引用次数: 10

Abstract

We investigate the problem of determining the trajectory that an observer should follow to be able to accurately track a target in a bearings-only measurements context. We assume that the target's motion is uniform and that the measurements are corrupted by an additive Gaussian white noise. Though, in theory, this process is observable if the observer maneuvers with turns or accelerations, the quality of the resulting estimation strongly depends on the trajectory chosen by the observer. In this paper, we present a numerical method to compute a trajectory of a maneuvering observer with the objective of maximizing the cumulative sum of bearing rates between the target and observer. Our approach is based on the piecewise stochastic control of a finite-horizon Markov process. A quantization method is applied to transform the problem into a discrete domain. We show that this transformation allows for a numerically tractable solution able to accurately track the target in a number of practical scenarios.
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基于量化的单方位跟踪观测器分段最优轨迹
我们研究了一个问题,确定一个观察者应该遵循的轨迹,以便能够在只有方位的测量环境中准确地跟踪目标。我们假设目标的运动是均匀的,并且测量结果受到加性高斯白噪声的干扰。虽然从理论上讲,这个过程是可以观察到的,如果观察者进行了转弯或加速的机动,结果估计的质量很大程度上取决于观察者选择的轨迹。本文提出了一种计算机动观测器轨迹的数值方法,其目标是使目标与观测器之间的承载率累积和最大化。我们的方法是基于有限视界马尔可夫过程的分段随机控制。采用量化方法将问题转化为离散域。我们表明,这种转换允许在许多实际情况下能够精确跟踪目标的数值易于处理的解决方案。
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