Research On Detection And Parameter Estimation Of Non-cooperative Direct Sequence Spread Spectrum Signals

Direct Sequence Spread Spectrum(DSSS)communication is an important spread spectrum communication method,which has excellent anti-interference ability,extremely low interception rate,and excellent confidentiality performance.Therefore,it has been widely used in fields such as satellite and radar communication.After intercepting non cooperative communication signals,in order to obtain the information contained in the signal,blind estimation of various feature parameters of the signal is necessary to provide parameter basis for communication countermeasures.This is an indispensable research topic in the field of communication countermeasures.The main research content of this article is signal detection and parameter estimation of DSSS signals under low signal-to-noise ratio conditions.Firstly,in the signal carrier frequency estimation section,the square multiplication method and cyclic spectrum method were analyzed.In response to the performance degradation of the square multiplication method under low signal-to-noise ratio,the relevant cumulative multiplication method was proposed.In the section of chip rate estimation,delay multiplication,cyclic spectrum method,and wavelet transform method were studied,and set averaging was used to reduce the impact of noise on the wavelet transform algorithm.In the section of pseudo code period estimation,time-domain correlation method,correlation cumulative second-order moment method,quadratic spectrum method,and cepstrum method were analyzed,and the estimation performance of the algorithms was compared.In the part of signal synchronization point estimation,eigenvalue decomposition method and matrix F norm method are used,and detailed theoretical analysis and simulation demonstration are carried out for the algorithms studied.Secondly,in response to the impact of random selection of initial clustering centers in the k-means algorithm on the estimation results of pseudo code sequences,a similarity measure is proposed to change the selection of initial clustering centers,which improves the stability of the algorithm in estimating pseudo code sequences.At the same time,the shortcomings of the k-means algorithm in asynchronous situations were analyzed,and it was proposed to introduce the wide window method and sliding window technology into the k-means algorithm to achieve the estimation of the pseudo code sequence of the unsynchronized signal.Finally,an offline platform for DSSS signal detection and parameter estimation was designed,and a simulation system and system user interface were built using Visual Studio.