Dsss Signal Code Sequence Recovery

The spread spectrum communication technologies have been widely used both in military and commercial telecommunication areas, owing to the ability of working at low signal-to-noise ratio (SNR), strong anti-jamming, difficult interception and mitigation of multi-path fading effects. The main work of this thesis is to research the blind recovery algorithms of Pseudo Noise (PN) sequence, which is applied to the direct sequence spread spectrum (DSSS) signal. Generally, the DS communication contains three parts, including blind detection, parameters estimation and recovery of spreading sequence. However, as the recovery of PN sequence influences the performance of the whole system, the research at this domain is quite urgent and significant at present.Firstly the previous and recent development of the recovery algorithms for PN sequence are summarized, then the basic theories are introduced and necessary experiments are given to verify the performance of all the mentioned approaches, finally appropriate comparison, analysis, explanation and conclusion are presented.The key work and innovations of this thesis mainly include:1. The systematic research of the current PN sequence recovery algorithms. The system mode is described with necessary details about the PN code sequence recovery theory which is based on the principal eigenvectors, as well as the recovery theory of the useful information. Several experiments are given to analyze the performance of the information code recovery, which is controlled by the PN sequence.2. Research of the classic modified sliding windows synchronization approaches and the typical subspace tracking algorithms. We first roughly introduced the synchronization and asynchronization signal modes, and then a large number of experiments are given to demonstrate the performance of the pre-mentioned algorithms.3. Modified the recovery algorithm which has better performance when the PN sequence is longer. By utilizing the subsection technique, the estimation and synchronization of PN sequence can be processed within each subsection, which greatly reduced the computational complexity without any obvious loss in correlation and convergency. Simulations verify the performance of the modified algorithm.4. Researched a new GEF-based blind recovery algorithm for the PN sequence. Generalized Energy Function (GEF) is able to estimate the principal eigenvectors with high precision and global stability, which can recover the PN sequence quickly and accurately at low SNR, and its convergence and correlation are better than subspace tracking algorithms, which is confirmed by the simulation experiments.5. Computer simulations are given to analyze all the correlated algorithms, including my modified algorithms. And then summarization of all the algorithms and their connections and properties are presented with the experiments data.