Open AccessWEAK SIGNAL DETECTION BASED ON MULTIPLE AUTO-CORRELATION TECHNIQUES
Author(s) -
S Sayed Mohammed,
Maher K. Mahmood
Publication year - 2021
Publication title -
journal of engineering and sustainable development
Language(s) - English
Resource type - Journals
eISSN - 2520-0925
pISSN - 2520-0917
DOI - 10.31272/jeasd.conf.2.1.8
Subject(s) - autocorrelation , correlation , false alarm , detection theory , signal (programming language) , computer science , noise (video) , matlab , pattern recognition (psychology) , statistics , signal to noise ratio (imaging) , algorithm , speech recognition , mathematics , artificial intelligence , detector , telecommunications , geometry , image (mathematics) , programming language , operating system
This study presents the performance of the auto-correlation methods for detecting weak signals, where the signal level is much less than the noise level. Double and triple auto-correlation techniques are used to improve the detection performance compared with the single autocorrelation. Simulation results obtained by MATLAB programs show that the multiple correlation techniques outperform the single correlation in terms of probability of detection and probability of false alarm versus signal to noise ratio SNR.