Joint path planning and sensor subset selection for multistatic sensor networks

R. Tharmarasa, T. Kirubarajan, T. Lang
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引用次数: 15

Abstract

Since inexpensive passive sensors have become available, it is possible to deploy a large number of them for tracking purposes in Anti-Submarine Warfare (ASW). However, modern submarines are quiet and difficult to track with passive sensors alone. Multistatic sensor networks, which have few transmitters (e.g., dipping sonars) in addition to passive receivers (e.g., sonobouys), have the potential to improve the tracking performance. The performance can be improved further by moving the transmitters according to existing target states and any possible new target states. Even though a large number of passive sensors are available, due to frequency, processing power and other physical limitations, only a few of them can be used at any one time. Then the problems are to decide the path of the transmitters and select a subset from the available passive sensors in order to optimize the tracking performance. In this paper, the Posterior Crame´r-Rao Lower Bound (PCRLB), which gives a lower bound on estimation uncertainty, is used as the performance measure. An algorithm is presented to decide jointly the optimal path of the movable transmitters, by considering transmitters' operational constraints, and the optimal subset of passive sensors that should be used at each time steps for tracking multiple, possibly time-varying, number of targets. The effect of sensor location uncertainties, due to deployment error and possible sensor drifting, on the tracking performance is addressed in the sensor management algorithm. Simulation results illustrating the performance of the proposed algorithm are presented.
多静态传感器网络的联合路径规划与传感器子集选择
由于廉价的无源传感器已经可用,在反潜战(ASW)中有可能部署大量用于跟踪目的。然而,现代潜艇非常安静,仅靠被动传感器很难跟踪。多静态传感器网络除了无源接收器(如声呐系统)外,还具有很少的发射器(如浸入式声呐系统),具有改善跟踪性能的潜力。通过根据现有目标状态和任何可能的新目标状态移动发射机,可以进一步提高性能。尽管有大量的无源传感器可用,但由于频率、处理能力和其他物理限制,每次只能使用其中的少数。接下来的问题是确定发射器的路径,并从可用的无源传感器中选择一个子集,以优化跟踪性能。本文采用给出估计不确定性下界的后验Crame´r-Rao下界(PCRLB)作为性能度量。在考虑发射机运行约束的基础上,提出了一种联合确定移动发射机最优路径的算法,并在每个时间步长中确定用于跟踪多个时变目标的无源传感器的最优子集。在传感器管理算法中,解决了由于部署误差和可能的传感器漂移导致的传感器位置不确定性对跟踪性能的影响。仿真结果说明了该算法的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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