Blind Estimation Of DSSS Signals Based On Feature Extraction And Least Square

Direct Sequence Spread Spectrum(DSSS)is one of the main ways of spread spectrum communication technology.In cooperative communication,the receiver can obtain the information sequence by use the pre-known spread spectrum sequence to despread the received signal.In non-cooperative communication,it is necessary to estimate the unknown spread spectrum sequence,so as to achieve the purpose of communication monitoring and electronic jamming.Therefore,the research of blind estimation for DSSS signal has been widely concerned.In this thesis,the spread spectrum sequence of DSSS signal and the blind estimation of information sequence has been studied.The main work includes the following aspects:1.When the SC-DSSS signal sequence is estimated blindly by singular value decomposition,the performance of estimation is unstable caused by the change of t he starting position of the received signal.Aiming at this problem,a SC-DSSS signal sequence blind estimation method for linear transformation of singular vectors was studied.The proposed method firstly constructs the signal matrix by split the received signal in a single(or double)spread spectrum period,and then performs a singular value decomposition on the matrix,and then perform a linear transformation on the right singular vector which corresponding to the two singular values whose size is closed,so as to get the information sequence estimation value,and extract the spread spectrum sequence estimation value from the corresponding left singular vector.2.In order to solve the problem that the periodic characteristics of the non-periodic long code-Direct Sequence Spread Spectrum(NPLC-DSSS)signal are severely damaged and the spread spectrum sequence is difficult to estimate,the similarity function based blind estimation problem of NPLC-DSSS signal spread spectrum sequence was studied.The proposed method firstly constructs the information code library in the single spread spectrum period with the known spreading period and the information chip width,then segments the NPLC-DSSS signal with the single spread spectrum period,changes the starting position by sliding,And the similarity analysis of the signals in the two spread spectrum cycles after the information code library is matched is used to estimate the synchronization position of the information code.And then the NPLC-DSSS signal which after synchronization and completion of the information code match is segmented by a single spreading period to construct a matrix,and the singular value decomposition of the matrix,the maximum left singular vector is the spread spectrum sequence estimation value.3.Aiming at the problem that the NPLC-DSSS signal spread spectrum sequence is difficult to estimate,an improved least squares algorithm is proposed to estimate the spread spectrum sequence of the synchronous multiuser NPLC-DSSS signal.The method first making the synchronous multiuser NPLC-DSSS signal equivalent to a synchronous multiuser SC-DSSS signal with missing data,and then constructs the missing data matrix.Afterwards,decompose the matrix by iterative least squares algorithm and the nested iterative method is used to compensate the missing parts until the iterative process converges,then the estimated values of the spread spectrum can be obtained.