A new acquisition method based on differential correlation
Sujuan Shang, Yanjun Hu, Jufeng Luo, Yingguan Wang · 2016
Acquisition is a key technology in DSSS system. The differential correlation is usually employed to eliminate the effect of frequency deviation. However, as the length of pseudo-code grows and the decrease of the SNR, the traditional differential acquisition algorithms will result in great loss of SNR. This paper presents an improved differential acquisition method, named as M-orders Auto-Correlation based on Differential correlation (MAC-DF). In the proposed method, the input signal is multiplied by the complex conjugate of the pseudo-code to eliminate its effect. After that, the product is applied to the M-orders Auto-Correlation to compensate the SNR loss caused by the differential process. By means of mathematical model to analyze its acquisition performance. We compare MAC-DF acquisition algorithm with the differential coherent and non-coherent acquisition algorithms through simulation. The simulation results indicate that this algorithm is approximately 5–6dB superior to the traditional differential acquisition algorithms in improving acquisition sensitivity and more adaptive to work under low SNR.