Target detection from dual disparate sonar platforms using canonical correlations

In this paper a new coherence-based feature extraction method for sonar imagery generated from two disparate sonar systems is developed. Canonical correlation analysis (CCA) is employed to identify coherent information from co-registered regions of interest (ROI's) that contain target activities, while at the same time extract useful coherent features from both images. The extracted features can be used for simultaneous detection and classification of target and non-target objects in the sonar images. In this study, a side-scan sonar that provides high resolution images with good target definition and a broadband sonar that generates low resolution images, but with reduced background clutter. The optimum Neyman-Pearson detector will be presented and then extended to the dual sensor platform scenarios. Test results of the proposed methods on a dual sonar imagery data set provided by the Naval Surface Warfare Center (NSWC) Panama City, FL will be presented. This database contains co-registered pair of images over the same target field with varying degree of detection difficulty and bottom clutter. The effectiveness of CCA as the optimum detection tool is demonstrated in terms of probability of detection and false alarm rate.

[1]  Louis L. Scharf,et al.  Low rank detectors for Gaussian random vectors , 1987, IEEE Trans. Acoust. Speech Signal Process..

[2]  Gerald J. Dobeck.  Fusing sonar images for mine detection and classification , 1999, Defense, Security, and Sensing.

[3]  Vinod Chandran,et al.  Detection of mines in acoustic images using higher order spectral features , 2002 .

[4]  S. C. Butler,et al.  Triply resonant broadband transducers , 2002, OCEANS '02 MTS/IEEE.

[5]  M.R. Azimi-Sadjadi,et al.  Canonical Coordinates for Detection and Classification of Underwater Objects From Sonar Imagery , 2007, OCEANS 2007 - Europe.

[6]  M.R. Azimi-Sadjadi,et al.  Undersea Target Classification Using Canonical Correlation Analysis , 2007, IEEE Journal of Oceanic Engineering.

[7]  N.A. Rimski-Korsakov,et al.  Simple digital system for side scan sonar data imaging , 1994, Proceedings of OCEANS'94.

[8]  W. H. Key,et al.  Side scan sonar technology , 2000, OCEANS 2000 MTS/IEEE Conference and Exhibition. Conference Proceedings (Cat. No.00CH37158).

[9]  Gerald J. Dobeck,et al.  Automated detection and classification of sea mines in sonar imagery , 1997, Defense, Security, and Sensing.

[10]  S. C. Butler.  High frequency triply resonant broadband transducer array development at NUWC , 2003, Oceans 2003. Celebrating the Past ... Teaming Toward the Future (IEEE Cat. No.03CH37492).

[11]  Gerald J. Dobeck,et al.  Adaptive-filter/feature-orthogonalization processing string for optimal LLRT mine classfication in side-scan sonar imagery , 1996, Defense, Security, and Sensing.

[12]  Louis L. Scharf,et al.  Canonical coordinates and the geometry of inference, rate, and capacity , 2000, IEEE Trans. Signal Process..