The .dsss / Bpsk Signal Spreading Code Sequence Estimation

The direct sequence spread spectrum (DSSS) signal has been widely used, owing to the ability of lower working signal-to-noise ratio (SNR), strong anti-jamming, lower probability interception and mitigating the effects of multi-path fading. So the DS communication counter technology becomes an urgent research topic in the electronic warfare field. The blind detection, parameters estimation and recovery of spreading sequences are the main contents of DS communication counter. After having estimated some signal parameters, it is an important approach to despread the DSSS signal and recover the primitive information by estimating the spreading sequences. Therefore the research on blind estimation of PN (Pseudo Noise) sequences shows the vital urgency and significance at present. This paper focuses on the blind code synchronization approach and spreading sequences estimation algorithm. The main results can be summarized as follows:1. Both synchronous and asynchronous DSSS/BPSK baseband signal models are established. Moreover two types of non-cooperative sequences estimation and despreading schemes are introduced briefly.2. Several usual blind code synchronization methods, including delay multiply (sliding autocorrelation), maximum norm and average noise reduction approaches are summed up and analyzed by computer simulations.3. A modified synchronization approach by using sliding windows is proposed. The pre-processing for obtaining principal eigenvectors is a smoothing procedure for the DSSS signal. The computer simulations show that the approach is more convenience in low SNR comparing with other code synchronization methods.4. The spreading sequences estimation algorithms based on linear feedback shift register (LFSR), matrix eigenvalue decomposition (EVD), neural networks (NN) have been systematically studied in this paper. And the performance of these algorithms is analyzed by many simulations.5. In order to solve the estimation problem of PN sequences itself, a code recovery algorithm based on subspace tracking is proposed. Base upon the projection...