Examines optimal sensor placement strategies for 3D target localization, highlighting effective methods.
This paper focuses on finding the optimal sensor placement strategies for circular time-of-arrival (TOA) localization in the three-dimensional (3D) space. The A-optimality criterion, minimizing the trace of the inverse Fisher information matrix (FIM), is applied to determine optimal sensor placements under the Gaussian measurement noise. A comprehensive analysis of optimal sensor-target geometries is provided in the general circumstance with no restriction on the number of sensors, sensor elevation angle and sensor-target range. The analysis is divided into two detailed sub-cases with uniform sensor measurement noise variance. The reachable minimum trace of Cramér-Rao lower bound (CRLB)= 9σ 2 /4N is derived. Two new closed-form solutions, i.e., the resistor network and special solution methods, are developed to quickly determine the optimal geometries. Furthermore, the theoretical smallest tr(CRLB)= 9 1 4(Σ i=1 N 1/σ2i ) -1 of using different noise variances is also presented. The analytical results are verified by simulation examples.
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Xu et al. (2019) studied this question.
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