Enemy Track Based Threat Assessment in Distributed Sensing Networks

Design of efficient distributed sensing/fusion networks involves issues such as sensor mobility, bandwidth capacity and reliability of communication links. Communication links between the sensors and fusion centers referred to as clusterheads are prone to jamming or foliage effects. In a recent paper, Patel et al. (2005) proposed a dynamic maximal expected coverage model for sensor networks operating under a uniform threat environment. This is useful in a situation where only the overall threat level is known. When enemy track information is available from sensors, it can be used to provide accurate assessments of threat probabilities, which vary in space and time. The first part of our work is in the calculation of these time/space dependent probabilities. We then enhance Patel et al.’s model by incorporating time dependent link failure probabilities. Computational studies involving packet level analysis are performed using OPNET network simulator, to study the benefit of using the revised threat probabilities. Results of a case study are presented, using a network centric warfare simulation testbed developed at the University at Buffalo. Both the computational and simulation results demonstrate that the track based topology management model is superior to the uniform threat topology model in terms of packets received (740% more), packets lost (7-50% less) and expected coverage (by 7.2%).