The Detection And Parameters Estimation Of Dsss Signals Based On Correlation And Cyclic Spectrum Method

The spread spectrum communication depended on good anti-interference ability, low probability of interception and the advantages of CDMA, was widely used in mobile communication, radar, navigation, orientation and other fields. In the area of non-cooperative communication such as communication reconnaissance and spectrum monitoring, owing to low SNR and lacking of priori knowledge, direct sequence spread spectrum(DSSS) signal detection and parameters estimation were difficult to achieve those have become an important issue.Since the bandwidth of DSSS signal was much larger than the bandwidth of baseband signal, thus energy of DSSS signal was distributed in the much wider bandwidth, power spectrum density was very low so as to submerge in the noise. These features made DSSS signal difficult to detect, or it was difficult to restore the information which was transmitted in the premise of the unknown pseudo-random(PN) sequence. This made the conventional approach invalid at low SNR. At present, there had been some methods for DSSS signal detection and parameters estimation. These methods were good for test results of single parameters. However, for DSSS signal, detection performance tended to deteriorate at low SNR.In this dissertation, time-domain correlation detection, delay-multiply, correlation cumulation, cyclic spectrum and other methods were considered. On the base of predecessors'studies, the improved methods were presented here.1. In the dissertation, in order to detect DSSS signal and estimate the period of PN, time-domain second-order moment detection was proposed based on time-domain correlation detection. The DSSS signal was cut up into several segments in this method, their correlation functions were obtained, and then the mean for superposition of square of correlation data was calculated. This method is able to suppress the additive white Gaussian noise so as to achieve an accurate estimation of the period of PN at low SNR.2. Based on delay-multiply detection, it indicated that the period of PN showed on the correlation domain, in addition, chip rate and carrier frequency displayed on the frequency domain. This method combined the formers with adaptive noise cancellation, correlation cumulation and spectrum correction in order to compose a detection system of time-domain delay correlation. It can estimate the period of PN, chip rate and carrier frequency accurately.3. In order to achieve DSSS signal detection and parameters estimation at lower SNR, cyclic statistics had the ability to suppress stationary noise based on cyclic spectrum theory. Improved set-average cyclic spectrum based on Welch method was proposed in this paper. DSSS signal that was divided into several sections used frequency smoothed cyclic periodogram algorithm, then the results for computing the mean were added up. This method used the envelope of cyclic spectrum to estimate the chip rate and carrier frequency, and it had high accuracy.The simulation showed that the aboved methods can achieve high precision at the low SNR in non-cooperative communication, and had important significance for blind despreading.