Low Signal To Noise Ratio Ds-ss/bpsk Signal Detection And Parameter Estimation Techniques

In this paper, the detection and parameter estimation, are studied for DS-SS/BPSK signal with low signal-to-noise ratio, including square detection, cyclic spectrum detection, correlation detection and higher-order statistics-based detection. The square detection, which was used in detection for DS-SS/BPSK signal between cooperations, is modified to estimate the frequency of non-cooperative weak DS-SS/BPSK signals with an acceptable performance. When combined with correlation accumulate technique and power spectrum collection-average technique, the temporal efficiency is enhanced. In the cyclic spectrum detection, the DS-SS/BPSK signal is modeled as cyclostationary signal. By searching the peaks on the slice of DS-SS/BPSK signals cyclic spectrum, the carrier frequency can be estimated. The correlation detection using the periodicity of the direct sequence autocorrelation function can estimate the symbol period at intermediate frequency or at baseband. Simulation results indicate that the former is superior to the latter when the demodulated frequency is unequal to the carrier frequency. The detection and parameter estimation based on high-order statistics are another approach for DS-SS/BPSK signals. In this paper, a sort of detectors based on fourth-order statistics slices are presented to detect the presence of signal and estimate the carrier frequency and symbol period of DS-SS/BPSK signal. Because the detector based on the fourth-order cumulant 2-D slice, which has better ability to suppress Gaussian noise, possesses both characters of square detector and correlation detector, it can estimate not only the carrier frequency, but also the symbol period.The above-mentioned detection and parameter estimation methods, but cyclic spectrum detection, have all been run in the real system and the results reach the desired indexes.