A self-organizing hybrid sensor system with distributed data fusion for intruder tracking and surveillance

A wireless sensor network is a network of distributed sensor nodes each equipped with its own sensors, computational resources and transceivers. These sensors are designed to be able to sense specific phenomenon over a large geographic area and communicate this information to the user. In this work a novel approach to tracking dynamic targets in a sensor field is presented. Using a combination of static and mobile sensor nodes we can track a target through the sensor field. Unlike other tracking methods that are based on computationally complex methods, the strategy adopted in this work is based on a computationally simple but effective technique of dividing the coverage region into grids based on the target location. The algorithms developed are based on a number of reasonable assumptions that are easily verified in a densely distributed sensor networks and require simple computations that efficiently tracks the target in the sensor field. The performance analysis of the tracking system is done on an experimental test-bed and also through simulation and the improvement in accuracy over other methods demonstrated.