Optimal sensor placement for multi-source AOA localisation with distance-dependent noise model

In this study, the optimal sensor placement problem for multi-source angle of arrival localisation is investigated. The authors adopt the A-optimality criterion, maximising the trace of Fisher information matrix, to determine the optimal sensor-target geometry under distance-dependent Gaussian noise model. A recursive representation of the Cramer-Rao lower bound is derived to recast the sensor placement problem into a sequential method, obtaining the optimal sensor geometries in a step by step manner. Note that the state-of-the-art methods are highly sensitive to the source location changes such that they should be relocated by any later changes in target geometries, which is practically impossible in systems with stationary receivers (such as radars). The proposed sequential method can circumvent this drawback by changing only one flexible sensor position rather than the whole geometry of the sensors. Numerical simulations are included to corroborate the theoretical results and determine the cost of such flexibility and robustness on the localisation performance.