Distributed sensor network for real time tracking
Proceedings of the fifth international conference on Autonomous agents
Detection, Tracking and Avoidance of Multiple Dynamic Objects
Journal of Intelligent and Robotic Systems
A framework and analysis for cooperative search using UAV swarms
Proceedings of the 2004 ACM symposium on Applied computing
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We present a framework for modeling and analysis for a surveillance network consisting of multiple sensors. Sensors monitor targets that crisscross a rectangular surveillance zone. When a sensor pursuits a target it leaves areas unguarded through which other targets can get past undetected. A methodology that computes the tracking time for a sensor such that a fraction of the targets expected to cross its home area is detected to an arbitrary probabilistic guarantee is presented based on the framework. Targets enter the surveillance zone according to Poisson statistics. The time spent by a target within a sensor's home area follows uniform random statistics. The home area of the sensor is the area guarded by it when it is stationed at its home position, its default position when it is not in pursuit of a target. The framework is further extended to situations where multiple sensors monitor the same home area. Simulation results presented corroborate with the probabilistic framework developed and verify its correctness for single as well as multi-sensor cases.