NEAR–OPTIMUM DETECTION OF SIGNALS IN UNDERWATER ACOUSTIC NOISE USING LOCALLY OPTIMAL DETECTOR IN TIGERS RIVER

Abstract

Signal detection has been considered important in under-water signal processing and digital communications, and depending upon noise statistics’ knowledge, near-optimum signal detections in the under-water acoustic noises (UWANs) may be realized in a more effective manner. The theory of the normal (i.e. Gaussian) noise permits using matched filter (MF) detectors; for that reason, a locally optimal (LO) detector has been designed in the present work for improving the probability of the detection ( based on knowing the probability density function (PDF) of noise. Under-water noise that has been utilized for the validation represents the real data that had been gathered from the sea with the use of the broad-band hydrophones at Abo Dali district -Kazem Al Ali Village-Tigris Beaches-Baghdad-Iraq. The LO detector performance is compared after that to the conventional matched filter detector and those have been assessed based on their values. For time-varying signals, the probability of false alarms has been identified as 0.010, and of 90%, energy-to-noise ratios (ENRs) of LO are more efficient compared to the ones of Matched Filter by 4.1dB and for the signals with a fixed frequency, LO is more efficient compared to matched filter by 4.7dB.

Keywords

• Underwater acoustic noise
• detection theory
• student’s t-distribution
• non-Gaussian signal detection