The Research On The DSSS Detection And Parameters Estimation

As a signal with random characteristic, large bandwidth, spread spectrum signal has strong discrimination ability, low probability of being intercepted and captured, so the spread spectrum technology is widely used in mobile communications, radar, navigation and orientation. Because spread spectrum communication has random characteristic and is always transmitted in low SNR environment, so how to capture it and estimate its parameters with little prior knowledge in low SNR has been an important research problem in electronic countermine field.Spread spectrum signal's specialities decide that it is difficult to find, even though the signal is detected, because the receiver doesn't know the spread sequence, the baseband signal is impossible to recover. But it is different from noise, they have difference in Time field, Frequency field, Power Spectrum, Cepstrum, Spectrum Correlation, High Order Spectrum and Time-Frequency field, we can detect it and estimate its parameters using corresponding methods.In this paper, we analysis correlation in time detection, cyclic spectrum detection and higher-order statistics-based detection, study their performance in signal detection and participation estimates of DSSS. Correlation in time detection can find the PN code period using the characteristics in time, this algorithm has a simple system and high detection speed, but the accuracy is limit. Cyclic spectrum detection can estimate carrier frequency and rate of the PN code exactly, but its calculation is large and system is complexity. Higher-order statistics-based detection can estimate carrier frequency and period of the PN code exactly, which has better ability to suppress Gaussian noise. Though this algorithm need large computation, we reduce system complexity greatly by using the 2D fourth-order cumulant.