Sparsity-Exploiting Anchor Placement for Localization in Sensor Networks

TL;DR

This paper presents a convex optimization approach for optimal sparse anchor placement in sensor network localization, considering energy efficiency and using CRB as a performance metric.

Contribution

It formulates the anchor placement as a convex optimization problem that accounts for sparsity and energy constraints, advancing localization design methods.

Findings

Efficient convex optimization solution for sparse anchor placement.

Joint ranging energy optimization with anchor placement.

Use of CRB as a performance constraint in localization.

Abstract

We consider the anchor placement problem in localization based on one-way ranging, in which either the sensor or the anchors send the ranging signals. The number of anchors deployed over a geographical area is generally sparse, and we show that the anchor placement can be formulated as the design of a sparse selection vector. Interestingly, the case in which the anchors send the ranging signals, results in a joint ranging energy optimization and anchor placement problem. We make abstraction of the localization algorithm and instead use the Cram\'er-Rao lower bound (CRB) as the performance constraint. The anchor placement problem is formulated as an elegant convex optimization problem which can be solved efficiently.