Target Tracking in Sensor Networks: the Focus of Attention Problem  PDF

Volkan Isler, John Spletzer, Sanjiv Khanna and Camillo J. Taylor

In this paper, we investigate data fusion techniques for target tracking using distributed sensors.  Specifically, we are interested in in how pairs of bearing or range sensors can be best assigned to targets in order minimize the expected error in the estimates. We refer to this as the focus of attention (FOA) problem.
In its general form, FOA is NP-hard and not well approximable.  However, for specific geometries we obtain significant approximation results: a 2-approximation algorithm for stereo cameras on a line, a PTAS for when the cameras are equidistant, and a 1.42 approximation for equally spaced range sensors on a circle.  By reposing as a maximization problem - where the goal is to maximize the number of tracks with bounded error - we are able to leverage results from maximum set-packing to render the problem approximable.  We demonstrate the results in simulation for a target tracking task, and for localizing a team of mobile agents in a sensor network.  These results provide insights into sensor/target assignment strategies, as well as sensor placement in a distributed network.

BibTeX entry:

AUTHOR = {V. Isler, J. Spletzer, S. Khanna, and C.J. Taylor},
TITLE = {Target Tracking in Sensor Networks: the Focus of Attention Problem},
YEAR = {2003},
BOOKTITLE = {Proceedings of the Conference on Intelligent Robots and Systems (IROS 2003)},
ADDDRESS = {Las Vegas, USA}