A New Low SNR Underwater Acoustic Signal Classification Method Based on Intrinsic Modal Features Maintaining Dimensionality Reduction

Abstract

The classification of low signal-to-noise ratio (SNR) underwater acoustic signals in complex acoustic environments and increasingly small target radiation noise is a hot research topic.. This paper proposes a new method for signal processing—low SNR underwater acoustic signal classification method (LSUASC)—based on intrinsic modal features maintaining dimensionality reduction. Using the LSUASC method, the underwater acoustic signal was first transformed with the Hilbert-Huang Transform (HHT) and the intrinsic mode was extracted. the intrinsic mode was then transformed into a corresponding Mel-frequency cepstrum coefficient (MFCC) to form a multidimensional feature vector of the low SNR acoustic signal. Next, a semi-supervised fuzzy rough Laplacian Eigenmap (SSFRLE) method was proposed to perform manifold dimension reduction (local sparse and discrete features of underwater acoustic signals can be maintained in the dimension reduction process) and principal component analysis (PCA) was adopted in the process of dimension reduction to define the reduced dimension adaptively. Finally, Fuzzy C-Means (FCMs), which are able to classify data with weak features was adopted to cluster the signal features after dimensionality reduction. The experimental results presented here show that the LSUASC method is able to classify low SNR underwater acoustic signals with high accuracy.

Application of Big Data Analysis in Cost Control of Marine Fishery Breeding

“…In the selection of seedlings and medicines, enterprises do not pay attention to establishing strategic alliances with suppliers of seedlings and medicines, which causes changes in the quality and price of raw materials. In the selection of feed, there is no attention to the nearby call feed, which will cause an increase in the amount of freight [29,30]. Secondly, the feeding process did not pay attention to the feed ratio, which also increased the cost.…”

Performance Comparison of ToA and TDOA Based Tracking In Underwater Multipath Environments Using Bernoulli Filter

“…The complexity of the underwater environment and smaller targets make the detection of underwater signals a challenging task. Detection of weak targets in low SNR scenarios has drawn attention in recent years [21], [22]in order to identify the enemy emission sonar source accurately. Using the digital watermarking technology and combining with the good time-frequency characteristics of fractional Fourier transform (FRFT.…”

An Acoustic Sea Glider for Deep-Sea Noise Profiling Using an Acoustic Vector Sensor

“…Low-frequency acoustic signals produced by tsunamis, undersea earthquakes, large mammals and artificial vessels are of increasing concern in the area of natural disaster monitoring and marine ecological protection [3], [4]. Moreover, the detection and identification of surface and underwater objects using acoustic sensors are another aspect of great concern in ship navigation [5], [6]. In order to achieve high-efficiency marine investigation and target detection, the integration of acoustic sensors on underwater moving platforms such as AUVs has become a new research hotspot [7], [8].…”