The fast capture of spread spectrum code is one of the key technologies of Direct Sequence Spread Spectrum (DSSS) communication. There are several traditional methods for the fast capture such as XFAST and AVERAGE. In this paper we propose a new algorithm based on the time domain samples and Binary search according the autocorrelation of the PN code. Firstly, signal's simple rate is reduced to a quarter of the chip rate with the received spread spectrum, and determined with a specific method, then the signal is divided into four parts by the local PN code and accumulated to a new sequence. Finally, the synchronous pseudo-code is captured with the correlation of the two new reference sequences. Experimental results demonstrate that the proposed algorithm significantly improves the efficiency in the capture of long Pseudo-Code code in DSSS, compared with traditional methods.
Proc. SPIE. 9091, Signal Processing, Sensor/Information Fusion, and Target Recognition XXIII
KEYWORDS: Signal to noise ratio, Lithium, Statistical analysis, Error analysis, Fourier transforms, Computer simulations, Monte Carlo methods, Data processing, Signal processing, Time-frequency analysis
Parameter estimation is an important component in the field of frequency-hopping communication. In particular, the accuracy and the efficiency of the hopping-cycle estimation is significant for these applications. The traditional time-frequency method, e.g., Short Time Fourier Transform, cannot work well with high resolution of both time and frequency, according to Heisenberg's uncertainty principle. In this paper we propose a novel algorithm which is based on Short Time Fourier Transform (STFT) and Sparse Linear Regression (SLR). Firstly, the signal is preprocessed by STFT and the information of peaks is extracted by a first-order differential method. Secondly, the hopping segment data is processed with the SLR according to the dual sparsity of time-frequency of the hopping signal. Finally, combining the statistical transition moments, an accurate estimate of the jump cycle is achieved. Simulation results demonstrate that the estimation algorithm is more accurate and efficient in low SNR than the traditional STFT.
To solve the problem of pulse sorting in complex electromagnetic environment, we propose an improved method for pulse sorting through in-depth analysis of the PRI transform algorithm principle and the advantages and disadvantages in this paper. The method is based on the traditional PRI transform algorithm, using spectral analysis of PRI transform spectrum to estimate the PRI centre value of jitter signal. Simulation results indicate that, the improved sorting method overcome the shortcomings of the traditional PRI jitter separation algorithm which cannot effectively sort jitter pulse sequence, in addition to the advantages of simple and accurate.