Optimal Sensor Placement for Multilateration Using Alternating Greedy Removal and Placement

Abstract

We present a novel algorithm for optimal sensor placement in multilateration problems. Our goal is to design a sensor network that achieves optimal localization accuracy anywhere in the covered region. We consider the discrete placement problem, where the possible locations of the sensors are selected from a discrete set. Thus, we obtain a combinatorial optimization problem instead of a continuous one. While at first, combinatorial optimization sounds like more effort, we present an algorithm that finds a globally optimal solution surprisingly quickly.