Research On Detection And Parameter Estimation Of The DSSS Signal With Negative SNR

Direct sequence spread spectrum(DSSS)communication systems have the characteristics ofwide spectrum, working at low Signal-to-Noise ratio(SNR), anti-interference, anti-multipatheffect, easily realizing code division multiple access(CDMA), low probability of intercept(LPI)and low probability of detection(LPD). DSSS signal has more virtues than conventionalcommunication systems and it is widely adopted in modern military and commercialcommunication systems, for example, CDMA communication system, Global PositioningSystem (GPS), measuring and control system, friend or foe identification, etc. Therefore, thecorresponding DSSS electronic counter technique becomes a key problem to be solved inelectronic warfare domain.For the issue of blind parameter estimation of DSSS signal contaminated by strong additivewhite Gaussian noise (AWGN), this dissertation mainly researches on the following methods:First, the algorithm of chip rate estimation using delay and multiply (DM) method is studied.The research object of traditional DM method is the base-band output by the delay andmultiplication processing or the base-band output component of medium frequency (IF)DSSS/BPSK signal by the delay and multiplication processing. Theoretical analysis indicatesthat the output of IF DSSS/BPSK signal by the delay and multiplication processing is composedof base-band and IF components. The base-band component contains information of chip rate,and IF component contains information of double carrier frequency. Through selecting differentdelay, chip rate and carrier frequency can be detected respectively. Thus, traditional DM methodis improved into multi-parameters estimation method. Combined with the autocorrelationprocessing technique, DM method can obtain lower SNR limitation of chip rate and carrierestimation.And next, detected technique of Duffing oscillator weak signal is introduced. Then bymaking use of Duffing oscillator's sensibility to small periodic signals and immunity againstnoise, the sine signal is detected which derives from square transform of DSSS/BPSK signal andis submerged in strong noise.The last part, a new theory and algorithm can be used in blind detection of the carrier wavesignal and the pseudo-random (PN) sequence of DSSS signal with negative SNR. First, without any priori knowledge of the DSSS signal, the carrier wave signal can be detected from DSSSsignal with negative SNR by using stochastic differential equations and energy detection method.Based on this, the pseudo-random sequence can also be blindly detected in DSSS signal withnegative SNR by reducing noise of the nonlinear signal and the algorithm of wavelet multi-scaledecomposition.Moreover, this research has conducted computer simulations of the above-mentioneddetection methods of the DSSS signal, provided simulation results, and analyzed theperformance of these detection methods discussed in this thesis.