通过融合多种传感测量，优化传感器布局以提升定位精度。
Optimal Sensor Placement Using Combinations of Hybrid Measurements for Source Localization
- 基于克拉美-罗下界推导传感器位置与定位精度关系
- 采用A-最优准则最小化估计均方误差，实现精度上限优化
- 针对TDOA/AOA/RSS/TOA等不同测量方式给出最优几何配置
本文研究静态源定位中多类型测量组合的最优传感器部署问题，涵盖到达时间差（TDOA）、接收信号强度（RSS）、到达角（AOA）和到达时间（TOA）等测量方式。由于传感器-源几何结构显著影响定位精度，论文系统性地提出基于混合测量的最优传感器布置策略。首先，通过推导克拉美-罗下界（CRB），建立传感器布设与源估计精度之间的数学关系；其次，选用A-最优准则（即最小化CRB矩阵的迹），统一计算可达的最小估计均方误差（MSE）；再次，针对TDOA、AOA、RSS和TOA等具体测量方式，理论推导并分析其最优几何约束；最后，通过仿真验证了新发现的有效性。
原文摘要 · Abstract (English)
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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