Fault Tolerant Target Localization and Tracking in Wireless Sensor Networks Using Binary Data

This paper investigates the use of a sensor network for localizing and tracking a moving target using only binary data. Due to the simple nature of the sensor nodes, sensing can be tampered (accidentally or maliciously), resulting in a significant number of sensor nodes reporting erroneous observations. Therefore, it is essential that any event tracking algorithm used in Wireless Sensor Networks (WSNs) exhibits fault tolerant behavior in order to tolerate a number of misbehaving nodes. SNAP (Subtract on Negative Add on Positive), is a simple event localization algorithm designed for WSNs applications that exhibits this fault tolerant behavior. The main contribution of this paper is to combine the decentralized implementation of SNAP with Kalman Filter techniques for tracking the movement of a target. This efficient tracking procedure provides fairly accurate results and turns out to be fault tolerant even when a large percentage of the sensor nodes report erroneous observations.