Pub Date : 2015-11-01DOI: 10.1109/SYMPOL.2015.7581170
P. S. Sridhar, A. Malarkodi, K. Nithyanandam, G. Latha
Directivity is the response of an electro acoustic transducer as a function of direction of the transmitted or incident acoustic wave in specified plane and at specified frequency [1]. Directivity pattern is a graphical description usually in polar coordinates [1]. This paper describes the establishment of directivity measurement system for an underwater electro-acoustic transducer. Motion controller in combination with the servo system is used to control the positioning of the transducer mounting mechanism and PXIe 6124-8 channel data acquisition system of National Instruments is used for data acquisition and analysis. LabVIEW programming is used for interface, control and recording data.
{"title":"Development of directivity measurement system for underwater acoustic transducers","authors":"P. S. Sridhar, A. Malarkodi, K. Nithyanandam, G. Latha","doi":"10.1109/SYMPOL.2015.7581170","DOIUrl":"https://doi.org/10.1109/SYMPOL.2015.7581170","url":null,"abstract":"Directivity is the response of an electro acoustic transducer as a function of direction of the transmitted or incident acoustic wave in specified plane and at specified frequency [1]. Directivity pattern is a graphical description usually in polar coordinates [1]. This paper describes the establishment of directivity measurement system for an underwater electro-acoustic transducer. Motion controller in combination with the servo system is used to control the positioning of the transducer mounting mechanism and PXIe 6124-8 channel data acquisition system of National Instruments is used for data acquisition and analysis. LabVIEW programming is used for interface, control and recording data.","PeriodicalId":127848,"journal":{"name":"2015 International Symposium on Ocean Electronics (SYMPOL)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129997687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-11-01DOI: 10.1109/SYMPOL.2015.7581165
Rithu James, M. Supriya
Sonar images are highly affected by signal-dependent multiplicative speckle noise. Denoising is required in sonar images to distinguish a number of different regions by analyzing the image. In this paper, we propose sonar image denoising based on a signal independent additive Gaussian noise model. The sparse representation of the sonar images is exploited in the denoising method. The noisy image, image patches and blocks of patches are denoised using Principal Component Analysis and Singular Value Decomposition methods. Comparison of different methods is done using different non reference image performance evaluation criteria.
{"title":"Sonar image denoising using adaptive processing of local patches","authors":"Rithu James, M. Supriya","doi":"10.1109/SYMPOL.2015.7581165","DOIUrl":"https://doi.org/10.1109/SYMPOL.2015.7581165","url":null,"abstract":"Sonar images are highly affected by signal-dependent multiplicative speckle noise. Denoising is required in sonar images to distinguish a number of different regions by analyzing the image. In this paper, we propose sonar image denoising based on a signal independent additive Gaussian noise model. The sparse representation of the sonar images is exploited in the denoising method. The noisy image, image patches and blocks of patches are denoised using Principal Component Analysis and Singular Value Decomposition methods. Comparison of different methods is done using different non reference image performance evaluation criteria.","PeriodicalId":127848,"journal":{"name":"2015 International Symposium on Ocean Electronics (SYMPOL)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125812169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-11-01DOI: 10.1109/SYMPOL.2015.7581161
N. Sireesha, K. Chithra, T. Sudhakar
The paper discusses the design, simulation and performance analysis of an adaptive filter based on Recursive Least Squares (RLS) algorithm with the main focus on mitigating the effect of multipath. The underwater acoustic channels are characterized by time-varying multipath propagation with large delay spreads which introduces severe intersymbol interference which can be equalized with the use of an adaptive filter. The filter behaviour is studied by simulating the multipath channel characteristics. The paper also analyzes the performance of the designed RLS adaptive filter in comparison to its Least Mean Square (LMS) counterpart.
{"title":"Performance analysis of linear recursive least squares adaptive filter to mitigate multipath effect","authors":"N. Sireesha, K. Chithra, T. Sudhakar","doi":"10.1109/SYMPOL.2015.7581161","DOIUrl":"https://doi.org/10.1109/SYMPOL.2015.7581161","url":null,"abstract":"The paper discusses the design, simulation and performance analysis of an adaptive filter based on Recursive Least Squares (RLS) algorithm with the main focus on mitigating the effect of multipath. The underwater acoustic channels are characterized by time-varying multipath propagation with large delay spreads which introduces severe intersymbol interference which can be equalized with the use of an adaptive filter. The filter behaviour is studied by simulating the multipath channel characteristics. The paper also analyzes the performance of the designed RLS adaptive filter in comparison to its Least Mean Square (LMS) counterpart.","PeriodicalId":127848,"journal":{"name":"2015 International Symposium on Ocean Electronics (SYMPOL)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125814793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-11-01DOI: 10.1109/SYMPOL.2015.7581173
Sayanti Bardhan, Shibu Jacob
This paper focuses on the performance of Multiple Signal Classification (MUSIC) and Estimation of Signal Parameters by Rotational Invariance techniques (ESPRIT) algorithm in real-time, for detection of underwater object by active sonar system of frequency 12 kHz. Experiment is conducted in Acoustic tank facility (ATF) at National Institute of Ocean Technology (NIOT). A table with dimension of 0.5mx0.5m is submerged in the tank at a depth of 3.6m from the water surface. A tow body with acoustic transmitter and hydrophone array is used to transmit and receive the acoustic signal in tank. The DOA estimation gives the exact location of the table in the tank. It is observed that the location of the submerged table computed by MUSIC & ESPRIT is comparable with a bias of about 1 degree.
{"title":"Experimental observation of direction-of-arrival (DOA) estimation algorithms in a tank environment for sonar application","authors":"Sayanti Bardhan, Shibu Jacob","doi":"10.1109/SYMPOL.2015.7581173","DOIUrl":"https://doi.org/10.1109/SYMPOL.2015.7581173","url":null,"abstract":"This paper focuses on the performance of Multiple Signal Classification (MUSIC) and Estimation of Signal Parameters by Rotational Invariance techniques (ESPRIT) algorithm in real-time, for detection of underwater object by active sonar system of frequency 12 kHz. Experiment is conducted in Acoustic tank facility (ATF) at National Institute of Ocean Technology (NIOT). A table with dimension of 0.5mx0.5m is submerged in the tank at a depth of 3.6m from the water surface. A tow body with acoustic transmitter and hydrophone array is used to transmit and receive the acoustic signal in tank. The DOA estimation gives the exact location of the table in the tank. It is observed that the location of the submerged table computed by MUSIC & ESPRIT is comparable with a bias of about 1 degree.","PeriodicalId":127848,"journal":{"name":"2015 International Symposium on Ocean Electronics (SYMPOL)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114798674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-11-01DOI: 10.1109/SYMPOL.2015.7581174
K. Kiran, S. Najeem, G. Latha
Acoustic vector sensor measures scalar acoustic pressure along with acoustic particle motion in three orthogonal directions. A single acoustic vector sensor provides information about the source direction than a scalar hydrophone. Thus acoustic vector sensors are widely used for many underwater acoustic applications. In this study an indigenously developed acoustic vector sensor array has been used to determine the direction of arrival in a controlled environment. Experiment has been conducted for different frequencies (1-6 kHz) and based on conventional beamforming technique DOA of the source was calculated. The experiment was repeated by changing the orientation of the vector sensor along different azimuthal directions at specific frequencies. The results obtained from the beamformer output compares well with the known source direction along the azimuth. The study clearly shows the application of underwater vector sensor in source localization and target tracking.
{"title":"Experimental result for direction of arrival (DOA) estimation using under water acoustic vector sensor.","authors":"K. Kiran, S. Najeem, G. Latha","doi":"10.1109/SYMPOL.2015.7581174","DOIUrl":"https://doi.org/10.1109/SYMPOL.2015.7581174","url":null,"abstract":"Acoustic vector sensor measures scalar acoustic pressure along with acoustic particle motion in three orthogonal directions. A single acoustic vector sensor provides information about the source direction than a scalar hydrophone. Thus acoustic vector sensors are widely used for many underwater acoustic applications. In this study an indigenously developed acoustic vector sensor array has been used to determine the direction of arrival in a controlled environment. Experiment has been conducted for different frequencies (1-6 kHz) and based on conventional beamforming technique DOA of the source was calculated. The experiment was repeated by changing the orientation of the vector sensor along different azimuthal directions at specific frequencies. The results obtained from the beamformer output compares well with the known source direction along the azimuth. The study clearly shows the application of underwater vector sensor in source localization and target tracking.","PeriodicalId":127848,"journal":{"name":"2015 International Symposium on Ocean Electronics (SYMPOL)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133867400","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-11-01DOI: 10.1109/SYMPOL.2015.7581164
B. Sherin, M. Supriya
Underwater target classification is a very demanding task owing to ever changing complicated nature of the underwater communication channels. Underwater target classification system identifies targets from a mixture of underwater events by its characteristic signature. The characteristic signatures pertaining to each target are patterned by feature recognition algorithms operating on hydrophone captured data. In this paper, an SVM target classifier is used to distinguish between targets of 4 acoustic classes. The performance of the classifier is improved by automating the selection of optimal algorithmic parameters. This paper attempts towards optimal selection of SVM parameters, kernel and kernel parameters using genetic algorithm.
{"title":"GA based selection and parameter optimization for an SVM based underwater target classifier","authors":"B. Sherin, M. Supriya","doi":"10.1109/SYMPOL.2015.7581164","DOIUrl":"https://doi.org/10.1109/SYMPOL.2015.7581164","url":null,"abstract":"Underwater target classification is a very demanding task owing to ever changing complicated nature of the underwater communication channels. Underwater target classification system identifies targets from a mixture of underwater events by its characteristic signature. The characteristic signatures pertaining to each target are patterned by feature recognition algorithms operating on hydrophone captured data. In this paper, an SVM target classifier is used to distinguish between targets of 4 acoustic classes. The performance of the classifier is improved by automating the selection of optimal algorithmic parameters. This paper attempts towards optimal selection of SVM parameters, kernel and kernel parameters using genetic algorithm.","PeriodicalId":127848,"journal":{"name":"2015 International Symposium on Ocean Electronics (SYMPOL)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133151993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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