A Monte Carlo Method for Joint Node Location and Maneuvering Target Tracking in a Sensor Network

We address the problem of tracking a maneuvering target that moves along a region monitored by a sensor network, whose nodes (including both the sensors and any data fusion centers, DFCs) are located at unknown positions. Thus, the node locations and the target track must be estimated jointly without the aid of beacons. We assume that the network consists of a collection of sensors and at least four DFCs. Each DFC collects and integrates the sensor measurements and can exchange data with the other DFCs. Within this setup, we propose a three-stage Monte Carlo method to (i) acquire rough initial estimates of the network node locations, (ii) track the target and refine the node position estimates individually at each DFC and (iii) fuse the results obtained by all the DFCs. The validity of the method is illustrated by computer simulations of a network of power-aware sensors and exactly four DFCs