Adaptive Acquisition Threshold Algorithm Based on Mean Energy

Abstract

An adaptive acquisition threshold algorithm based on mean energy (MEAT) was proposed. Conditional probability of acquisition decision variable in MEAT was analyzed under the two hypotheses of synchronization and non-synchronization, and its false alarm probability and detection probability were deduced. Then simulation on Direct-Sequence Spread-Spectrum (DSSS) system using MEAT was made whose result shows the Constant False Alarm Rate (CFAR) characteristic of MEAT and the improvement of detection probability of MEAT relative to traditional fixed threshold algorithm.