Zhao Zhi-Jin, Gu Xiao-Wei, Shen Lei. An Identification Method of Long Pseudo-random Code Sequence in Non-periodic Direct Sequence Spread Spectral Signals[J]. Journal of Electronics & Information Technology, 2014, 36(8): 1792-1797. doi: 10.3724/SP.J.1146.2013.01454
Citation:
Zhao Zhi-Jin, Gu Xiao-Wei, Shen Lei. An Identification Method of Long Pseudo-random Code Sequence in Non-periodic Direct Sequence Spread Spectral Signals[J]. Journal of Electronics & Information Technology, 2014, 36(8): 1792-1797. doi: 10.3724/SP.J.1146.2013.01454
Zhao Zhi-Jin, Gu Xiao-Wei, Shen Lei. An Identification Method of Long Pseudo-random Code Sequence in Non-periodic Direct Sequence Spread Spectral Signals[J]. Journal of Electronics & Information Technology, 2014, 36(8): 1792-1797. doi: 10.3724/SP.J.1146.2013.01454
Citation:
Zhao Zhi-Jin, Gu Xiao-Wei, Shen Lei. An Identification Method of Long Pseudo-random Code Sequence in Non-periodic Direct Sequence Spread Spectral Signals[J]. Journal of Electronics & Information Technology, 2014, 36(8): 1792-1797. doi: 10.3724/SP.J.1146.2013.01454
Using the second-order and third-order autocorrelation characteristics of m sequences, the maximum likehood estimation for the triple autocorrelation function of the Non-Periodic Long Code Direct Sequence Spread Spectral (NPLCDS-SS) signals is deduced. By utilizing the shift-and-add property and the triple autocorrelation characteristics of m sequences, the influence of the information code on the estimation is eliminated by the processing of delay and multiplication, a identification method for long code is proposed based on the peaks of the triple autocorrelation function in a non-cooperative communication with the certain carrier frequency and chip width of spreading code. Simulations under additive white Gaussian noise show that the correct identification probability of the algorithm is above90% when a quarter of the cycle length of the long PN code signal is used only and the signal-to-noise ratio is greater than 3.5 dB.