In order to raise the detection precision of the extended binary phase shift keying （EBPSK） receiver, a detector based on the improved particle swarm optimization algorithm （IMPSO） and the BP neural network is designed. First, the characteristics of EBPSK modulated signals and the special filtering mechanism of the impacting filter are demonstrated. Secondly, an improved particle swarm optimization algorithm based on the logistic chaos disturbance operator and the Cauchy mutation operator is proposed, and the EBPSK detector is designed by utilizing the IMPSO-BP neural network. Finally, the simulation of the EBPSK detector based on the MPSO-BP neural network is conducted and the result is compared with that of the adaptive threshold-based decision, the BP neural network, and the PSO-BP detector, respectively. Simulation results show that the detection performance of the EBPSK detector based on the IMPSO-BP neural network is better than those of the other three detectors.
