Cooperative detection of moving targets in wireless sensor network based on fuzzy dynamic weighted majority voting decision fusion

Multisensor data fusion has many military and civilian applications due to its statistical advantages. In this work, we propose a heuristic to enhance cooperative detection of moving targets within a region that is monitored by a wireless sensor network. This heuristic is based on fuzzy dynamic weighted majority voting for decision fusion. It fuses all the local decisions of the neighboring sensor nodes and determines the number and types of moving targets. A fuzzy logic weights each local decision based on the signal to noise ratio of the acoustic signal for target detection and the signal to noise ratio of the radio signal for sensor communication. The spatial correlation among the observations of neighboring sensor nodes is efficiently utilized. In addition, a finite state machine is proposed to reduce the detection false alarm and to estimate the best time at which the cluster decisions should be reported to the sink or gateway. Simulation results show that there is an optimal sensor number for distributed detection of a random process. This work is compared with the normal majority voting algorithm for hard decision fusion. It shows that the fuzzy weighted majority voting for decision fusion has less detection error than the normal majority voting.