Paper Info
Title
An Acoustic Signal Enhancement Method Based on Independent Vector Analysis for Moving Target Classification in the Wild.
Abstract
In this paper, we study how to improve the performance of moving target classification by using an acoustic signal enhancement method based on independent vector analysis (IVA) in the unattended ground sensor (UGS) system. Inspired by the IVA algorithm, we propose an improved IVA method based on a microphone array for acoustic signal enhancement in the wild, which adopts a particular multivariate generalized Gaussian distribution as the source prior, an adaptive variable step strategy for the learning algorithm and discrete cosine transform (DCT) to convert the time domain observed signals to the frequency domain. We term the proposed method as DCT-G-IVA. Moreover, we design a target classification system using the improved IVA method for signal enhancement in the UGS system. Different experiments are conducted to evaluate the proposed method for acoustic signal enhancement by comparing with the baseline methods in our classification system under different wild environments. The experimental results validate the superiority of the DCT-G-IVA enhancement method in the classification system for moving targets in the presence of dynamic wind noise.
Year
DOI
Venue
2017
10.3390/s17102224
SENSORS
Keywords
Field
DocType
signal enhancement,independent vector analysis,acoustic target classification,microphone array
Frequency domain,Time domain,Pattern recognition,Discrete cosine transform,Unattended ground sensor,Signal enhancement,Electronic engineering,Microphone array,Artificial intelligence,Independent vector analysis,Engineering,Generalized normal distribution
Journal
Volume
Issue
ISSN
17
10.0
1424-8220
Citations 
PageRank 
References 
1
0.35
32
Authors
6
Name
Order
Citations
PageRank
Qin Zhao1256.84
feng guo2253.88
Xingshui Zu3132.28
Yuchao Chang410.35
Baoqing Li511420.13
Xiaobing Yuan6193.49