Parameter Estimation Of DSSS Signal, Demodulation And DSP Implementation

Direct sequence spread spectrum (DSSS) signal has been widely used in military and commercial communication systems because of its low probability of intercepting, anti-interference and anti-multipath effect. Because DSSS signal is always submerged in strong noise, detection and parameter estimation of DSSS signal are difficult in the non-cooperative communications.This thesis focuses on studying blind parameter estimation, demodulation and implementation problems of DSSS signal. Firstly, it introduces the basic theory of spread spectrum communication and summarizes the process of DSSS signal’s sending and receiving. Secondly, we study the methods of blind parameter estimation. In these methods, the square detection is used to estimate the carrier frequency. The chip rate can be estimated by using the cyclic auto-correlation algorithm. Both reprocessed power spectrum method and auto-correlation algorithm in time domain can be used to estimate the pseudo-code period. In addition, the maximum norm method is applied to capture signals and subspace decomposition algorithm is used to recover pseudo-code from the received signal. Then, we can use Costas phase lock loop to demodulate DSSS signal. At last, the thesis details how to achieve above algorithms on the TMS320C6713platform and verifies the correctness of these algorithms.