WEAK SIGNAL DETECTION BASED ON MULTIPLE AUTO-CORRELATION TECHNIQUES | Zendy

Sarah S. Mohammed | Zendy; Maher K. Mahmood | Zendy

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WEAK SIGNAL DETECTION BASED ON MULTIPLE AUTO-CORRELATION TECHNIQUES

Author(s) -

Sarah S. 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 , 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.

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