DSSS Signal Parameter Detection and PN Sequence Estimation Based on SOFM Neural Network
Cheng Hao, Guo Wei, Jingdong Yu · 2006
Having not the a prior knowledge about the DSSS signal in the non-cooperation condition, we utilize a self-organizing feature map (SOFM) neural network algorithm to detection and identify the PN sequence. A new method that is suit DSSS signal is proposed according the Kohonen rule in SOFM theory. Utilizing the characteristic based on non-supervised learning rule, the blind algorithm can estimation the PN sequence in low SNR. The computer simulation and experiment test demonstrated that the algorithm is effective. Comparing the traditional slip-correlation method, the SOFM algorithm's BER and implementation complexity is lower