Interception And Analysis Of DSSS Signals Under Aliasing Conditions

As a communication technology that reduces the signal-to-noise ratio(SNR)by extending the signal bandwidth in the frequency domain,direct sequence spread spectrum(DSSS)is widely used in military and civil communications due to its advantages such as wide frequency band,low power,good confidentiality,low interception rate and code division multiple access.In the non-cooperative reception,such as communication reconnaissance,radio spectrum monitoring and positioning,and tracking of illegal communication stations,it is of great practical significance and research value to intercept and analyze such signals.Although much progress has been made in blind analysis of DSSS signals,they are all based on the single DSSS signal.When there are co-frequency strong power interference signals of other communication systems in the non-cooperative environment,or when the partner adopts the asymmetric paired carrier multiple access communication system and uses the DSSS signal in the small station in order to improve confidentiality or realize multi-user transmission,the DSSS signals intercepted by the non-partners are aliasing signals with strong interference signal.The above aliasing conditions,coupled with multipath interference,complex phase modulation,etc.,make the detection and blind analysis of DSSS signals extremely challenging.This article mainly focuses on the blind analysis of DSSS signals under aliasing conditions,and makes the following researches:1.The cancellation technology of the strong interference for DSSS signals under aliasing condition is studied.Two cases of narrowband interference and broadband interference are discussed separately.Among them,focusing on the DSSS signals with aliasing narrowband interference,an interference cancellation algorithm based on complementary symmetric filter is proposed;thus,the influence of the parameters of the algorithm and signals on the performance of the algorithm is studied.The simulation results show that the proposed algorithm can achieve high-precision of interference cancellation for the DSSS signals that are aliased with interference signals with strong power and narrow bandwidth.In addition,the realization of the proposed algorithm has many application prospects,such as wideband multi-signal cancellation,channel estimation and spread spectrum detection under covert transmission.2.The detection and parameter estimation of DSSS signals after eliminating the strong interference signal are studied.For the multiple phase shift keying modulation(MPSK)and continuous phase modulation(CPM),three types of detectors with parameter estimation are discussed respectively,that is,carrier frequency detector,chip rate detector,and spread spectrum(PN)code period detector.Firstly,for the signal detection and carrier frequency estimation,the frequency multiplier detector and cyclic spectrum detector are discussed.Among them,the characteristics of cyclic spectrum are analyzed and deduced in detail;then,the performance of two detectors for the MPSK and CPM is discussed.Secondly,for the signal detection and chip rate estimation,the delay multiplication algorithm for the MPSK is first studied,and the effect of delay parameters on its performance is analyzed through simulations.Then,an estimation algorithm based on wavelet time-frequency analysis is proposed for the CPM.The algorithm is suitable for the flexible modulation parameters of CPM.Thirdly,for the signal detection and PN code period estimation,the mature algorithms,autocorrelation fluctuation and second power spectrum are discussed.The performance difference for the MPSK between them is first discussed;then,their applicability and performance changes for the CPM are analyzed.3.For short-code DSSS signals,the PN code estimation under Gaussian channels and multipath channels are studied respectively.Firstly,for the Gaussian channel,three mature algorithms,matrix decomposition,subspace tracking and neural network,are compared and discussed.Among them,the matrix decomposition performs best and can reach the cramer-rao bound(CRB),but its computational complexity is high and tracking capability is poor.The subspace tracking and neural network algorithms can avoid the above-mentioned problems,but their performance suffers.Secondly,for the multipath channel,a joint blind estimation algorithm of PN codes and channels based on the maximum likelihood method is proposed.In order to reduce the influence of the error of channel estimation on PN code estimation under low SNR,an improved joint estimation method is proposed.Moreover,to measure the channel estimation performance of the algorithm rigorously,the CRB of channel estimation in the cooperative communication is derived.The proposed algorithm is not limited by the PN code pattern.The simulation results show that the performance of the PN code estimation of the algorithm is equivalent to that of the maximum likelihood estimation of the PN code based on the known channels in the ideal case,and the performance of the channel estimation is close to the CRB in cooperative communication.4.For long-code DSSS signals,the PN code estimation under Gaussian channels and multipath channels are studied respectively.Firstly,for the Gaussian channel,two processing methods suitable for complex non-periodic long-code DSSS signals are compared and analyzed,that is,the optimization method based on the transformation of the missing data model and the matrix decomposition method based on the overlapping segments by using narrow windows.Among them,the optimization method can approximate the CRB of PN code estimation,while the decomposition method has slightly lower performance due to its probability approximation.Secondly,for the multipath channel,a joint blind estimation algorithm of PN code and channels is proposed.To avoid some problems such as the matrix inversion,an adaptive optimization method of the algorithm is given.In addition,in order to reduce the computational complexity and improve the estimation performance of the algorithm under low SNR,a low-complexity joint blind estimation algorithm based on an approximate model is further proposed.The simulation results show that for channel estimation,the performance of the proposed methods is better than the semi-blind algorithms based on known PN codes;for PN code estimation,the performance of the proposed methods is better than that of the blind estimation algorithms in Gaussian channels based on known multipath channel equalization.