Serial PN Acquisition Using Smart Antenna and Censored Mean Level CFAR Adaptive Thresholding for a DS/CDMA Mobile Communication

A robust auto‐adaptive approach for serial acquisition of generalized multi‐carrier spread spectrum in multipath fading mobile channels

“…For this reason, a large number of different adaptive threshold mechanisms known in the Radar systems have been applied to the code acquisition problems, where these mechanisms are based on constant false alarm rate (CFAR) algorithms that are used to determine the threshold value according to the actual environmental conditions. [7][8][9][10][11][12][13] As the arithmetic averaging CFAR detector and its modifications [8][9][10] suffer a serious detection performance degradation when the reference window used to estimate the background noise level is infected by interfering signals, 11 a variety of alternatives have been proposed to develop CFAR detectors applied to the PN code acquisition to overcome these drawbacks. These alternatives include the fixed point(s) censoring CFAR detectors, where the largest ranked cells are censored, and only the remaining ranked cells are used to estimate the background noise level.…”

“…These alternatives include the fixed point(s) censoring CFAR detectors, where the largest ranked cells are censored, and only the remaining ranked cells are used to estimate the background noise level. 2,[11][12][13] The fixed censoring point CFAR detectors are effective against the appearance of interfering signals in the reference window, as long as they are disposed of properly. This implies that to censor the unwanted ranked cells, which may not be available in many applications, some prior information about the background environment is needed.…”

Pn Code Acquisition Using Smart Antenna and Adaptive Thresholding Cfar Based on Ordered Data Variability for Cdma Communications

“…It is well known that the performance of the conventional CA-CFAR detector, which is suboptimum in a homogeneous environment and is equivalent to the optimum Neyman-Pearson detector as the number of reference cells increases, is serious degraded in the presence of multipath. However, to overcome this problem, many alternative CFAR processors have been proposed in the literature, and in particular order statistics (OS) based CFAR processor proved to be more robust [14][15][16][17][18][19][20][21]. In OS-CFAR processing, the references cells are rank ordered in an ascending order according to their magnitude.…”

“…The OS-CFAR processor considered in [4] estimates the background noise power from kth smallest cell in the reference window. In the censored mean level detector (CMLD) CFAR considered in [15,16] some largest range cells are censored from the reference window and the threshold is computed from the remaining cells. The CMLD is robust against multipath interference as long as the number of censored cells exceeds the number of multipath interference.…”

“…They used the trimmed-mean (TM) CFAR processor for adaptive thresholding [14]. The same acquisition system was adopted in [15], but using the censored mean level detector CMLD-CFAR [16] in a Rayleigh fading multipath channel. The above mentioned systems used adaptive order statistic detection based on a fixed censoring point and they perform robustly as long as the interferences are properly discarded.…”