Online decision fusion method for target detection based on sensor networks

To solve the problem that the fusion center in a sensor network (SN) cannot completely obtain the local detection performance indices, a target detection model based on the SN is established. An online decision fusion method for target detection with the non-ideal channel between local sensors and the fusion center is proposed. This method constructs the model of solving unknown parameters including local false alarm probabilities, local detection probabilities and the average bit error probability of the non-ideal transmission channels. The nonlinear least square method is employed to estimate the unknown parameters. In order to maximize the system detection performance, the sensors with high detection performance are chosen to participate in the fusion. The simulation results show that the estimations tend to be with the true local probability values and the average bit error probability. Compared with the optimal likelihood ratio (LR) based fusion rule, the proposed online decision fusion method exhibits only slight performance degradation.