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Optimal Sensor Placement Using Combinations of Hybrid Measurements for Source Localization

Abstract

This paper focuses on static source localization employing different combinations of measurements, including time-difference-of-arrival (TDOA), received-signal-strength (RSS), angle-of-arrival (AOA), and time-of-arrival (TOA) measurements. Since sensor-source geometry significantly impacts localization accuracy, the strategies of optimal sensor placement are proposed systematically using combinations of hybrid measurements. Firstly, the relationship between sensor placement and source estimation accuracy is formulated by a derived Cramér-Rao bound (CRB). Secondly, the A-optimality criterion, i.e., minimizing the trace of the CRB, is selected to calculate the smallest reachable estimation mean-squared-error (MSE) in a unified manner. Thirdly, the optimal sensor placement strategies are developed to achieve the optimal estimation bound. Specifically, the specific constraints of the optimal geometries deduced by specific measurement, i.e., TDOA, AOA, RSS, and TOA, are found and discussed theoretically. Finally, the new findings are verified by simulation studies.

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@article{tang2025_2504.03769,
  title={ Optimal Sensor Placement Using Combinations of Hybrid Measurements for Source Localization },
  author={ Kang Tang and Sheng Xu and Yuqi Yang and He Kong and Yongsheng Ma },
  journal={arXiv preprint arXiv:2504.03769},
  year={ 2025 }
}
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