Application of BP neural network based PN code acquisition system in underwater DSSS acoustic communication

In this paper, a modified Back Propagation (BP) neural network based PN code acquisition system is presented. Conventional neural network based acquisition systems are usually trained on PN code, but this system is based on training a Back Propagation neural network at all possible phase of the output of correlation detector which is modified by a recursive accumulator. The recursive accumulator can converge the input of neural network into a limited sample space, and BP neural network will acquire the phase of received PN code from the converged data. The advantages of this system are that the gain of system is controllable and the sample space of training data is limited. The BP neural network is used to distinguish the transmitted signal and noise. Computer simulations show that the proposed system can acquire the phase of the received PN code correctly at very low Signal to Noise Ratio (SNR) in AWGN channel and underwater acoustic channel.