By Sergio Rui Silva
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Extra info for Advances in Sonar Technology (2009)
Pokharel, P. ; Principe, J. C.. (2006). “Correntropy: A Localized Similarity Measure”, International Joint Conference on Neural Networks, 2006, pp. 4919 – 4924. ; Taylor, N. (1998). 2, 28 Sep-1 Oct 1998. Nelson, M. A. (1998). “DARPA Synthetic Aperture Sonar”, Proceedings of the Adaptive Sensor Array Processing (ASAP) Workshop, vol. 1, pp. 141-155, 15 May 1998. ; Rognstad, M. (1996) “Acoustic Detection and Classification of Burried Unexploded Ordinance (UXO) Using Synthetic Aperture Sonar”, PACON’ 96, 1996.
These parameters are weighted together with the image metric and serve as a cost function for the optimization algorithm to search the solution space (Fig. 18). Nevertheless, these errors are hardly ever smaller than the original signal wavelength, and so create a solution surface that is difficult to search for the optimum set of parameters. However, if we have access to the raw data, by dividing the received signal bandwidth in several smaller bands and conjugate complex multiplying the pulse compressed signals obtained in each band one by the other, a new resulting signal is obtained with an effective longer wavelength corresponding to the frequency difference between the two sub-bands ([Silva, S.
Gumerov, N. ; Davis, L. (2003). “Improved Fast Gauss Transform and Efficient Kernel Density Estimation”, Proceedings of the Ninth IEEE International Conference on Computer Vision (ICCV’03), 2003, pp. 1. 3 Motion Compensation in High Resolution Synthetic Aperture Sonar (SAS) Images R. Heremans, Y. Dupont and M. Acheroy Signal and Image Center (SIC-RMA) Belgium 1. Introduction The sequence of echoes detected by an active Synthetic Aperture Sonar (SAS) is coherently added in an appropriate way to produce an image with greatly enhanced resolution in the azimuth, or along-track direction when compared with an image obtained from a standard Side Looking Sonar (SLS).
Advances in Sonar Technology (2009) by Sergio Rui Silva