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用于解决具有距离相关噪声的水下航行器定位的最优传感器布置问题的遗传算法。

Genetic Algorithm to Solve Optimal Sensor Placement for Underwater Vehicle Localization with Range Dependent Noises.

作者信息

Villa Murillo, Ferreira Bruno, Cruz Nuno

机构信息

INESC TEC-Institute for Systems and Computer Engineering, Technology and Science, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 378, 4200-465 Porto, Portugal.

出版信息

Sensors (Basel). 2022 Sep 22;22(19):7205. doi: 10.3390/s22197205.

DOI:10.3390/s22197205
PMID:36236304
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9570755/
Abstract

In source localization problems, the relative geometry between sensors and source will influence the localization performance. The optimum configuration of sensors depends on the measurements used for the source location estimation, how these measurements are affected by noise, the positions of the source, and the criteria used to evaluate the localization performance. This paper addresses the problem of optimum sensor placement in a plane for the localization of an underwater vehicle moving in 3D. We consider sets of sensors that measure the distance to the vehicle and model the measurement noises with distance dependent covariances. We develop a genetic algorithm and analyze both single and multi-objective problems. In the former, we consider as the evaluation metric the arithmetic average along the vehicle trajectory of the maximum eigenvalue of the inverse of the Fisher information matrix. In the latter, we estimate the Pareto front of pairs of common criteria based on the Fisher information matrix and analyze the evolution of the sensor positioning for the different criteria. To validate the algorithm, we initially compare results with a case with a known optimal solution and constant measurement covariances, obtaining deviations from the optimal less than 0.1%. Posterior, we present results for an underwater vehicle performing a lawn-mower maneuver and a spiral descent maneuver. We also present results restricting the allowed positions for the sensors.

摘要

在源定位问题中，传感器与源之间的相对几何关系会影响定位性能。传感器的最优配置取决于用于源位置估计的测量值、这些测量值如何受到噪声影响、源的位置以及用于评估定位性能的标准。本文解决了在平面中为三维移动的水下航行器进行定位时的最优传感器放置问题。我们考虑测量到航行器距离的传感器组，并使用与距离相关的协方差对测量噪声进行建模。我们开发了一种遗传算法，并分析了单目标和多目标问题。在单目标问题中，我们将费希尔信息矩阵逆矩阵的最大特征值沿航行器轨迹的算术平均值作为评估指标。在多目标问题中，我们基于费希尔信息矩阵估计常见标准对的帕累托前沿，并分析不同标准下传感器定位的演变。为了验证该算法，我们首先将结果与具有已知最优解和恒定测量协方差的情况进行比较，得到与最优解的偏差小于0.1%。之后，我们给出了水下航行器执行割草机动和螺旋下降机动的结果。我们还给出了限制传感器允许位置的结果。

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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c19/9570755/df2ee4b05426/sensors-22-07205-g0A12.jpg
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Sensors (Basel). 2019 Sep 9;19(18):3880. doi: 10.3390/s19183880.
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Optimal sensor placement for multiple target positioning with range-only measurements in two-dimensional scenarios.二维场景中仅使用距离测量进行多个目标定位的最优传感器放置。
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Sensor networks for optimal target localization with bearings-only measurements in constrained three-dimensional scenarios.基于方位角测量的约束三维场景中最优目标定位的传感器网络。
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