Sensor Resource Allocation for Tracking Using Outer Approximation

Abstract

In this letter, we consider the problem of activating the optimal combination of sensors to track a target moving through a network of sensors. Our objective is to minimize the predicted approximate error in the target position estimate subject to constraints on sensor usage and sensor-usage costs. We formulate the scheduling problem as a binary convex programming problem and solve it using the outer approximation (OA) algorithm. We apply the proposed OA scheduling method to the scenario of tracking an underwater target using a network of active sensors. We demonstrate using Monte Carlo simulations that our OA scheduling method obtains optimal solutions to scheduling problems of up to 70 sensors in the order of seconds