Spread-based Heuristic for Sensor Selection in Sensor Networks

In this paper we propose a method for selecting an appropriate subset of sensors with a view to minimize estimation error while tracking a target with sensors spread across in a 2-dimensional plane. In particular, we address the problem of "given N sensors, select n<N sensors to improve the given estimate of target location". Only the selected sensors need to measure distance to the target and communicate the same to the central "tracker". This minimizes the bandwidth and energy consumed in measurement and communication while achieving near minimum estimation error. In this paper, we have proposed that the sensors be selected based on three measures viz. (a) collinearity, (b) spread, and (c) proximity to the target. We use least square error estimation technique to compute the target location using distance measurements subject to multiplicative errors from multiple sensors