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http://theses.ncl.ac.uk/jspui/handle/10443/1220
Title: | Broadband, ultra-sparse array processing for low complexity multibeam sonar imaging |
Authors: | Menon, Raghav |
Issue Date: | 2011 |
Publisher: | Newcastle University |
Abstract: | Imaging sonar systems have become increasingly popular in numerous applications associated with underwater imaging. Though multibeam sonar systems have been used in a variety of applications, the cost of these systems limits their use. The reason for the high costs has been identified to the use of large number of hydrophone array elements and hence large number of associated analogue channels and analogue-to-digital converters (ADC) that are required in high resolution imaging. In this thesis, an imaging sonar system has been developed with as few as four array elements to minimise cost. The inter-element spacing between any two array elements was chosen to be much greater than half the wavelength. In order to avoid phase ambiguity associated with wide array element spacing, the time difference of arrival is determined. Hence, for this purpose a wideband chirp signal was used. The return signals were divided into range cells to determine the target range. The time difference of arrival was obtained by correlating the range cells. Using the time difference of arrival, the direction of arrival (DOA) angle was calculated. The image of the target being illuminated was formed using the calculated range and the DOA values. The image pixel intensity at any pixel position was determined from the correlation result between the range cells. A simulation model was built to test the theory developed. Simulations were performed for various inter-element spacing and for four different target profiles types. Two objective metrics (signal to noise (SNR) ratio and peak signal to noise (PSNR) ratio) and a subjective metric (Structural Similarity (SSIM) index) were used to determine the performance of the algorithm and image quality. Image formed from the simulations using two hydrophone elements showed the presence of artefacts in the form of correlation sidelobes. The SNR metric showed a low gain of -5dB on comparison against a test image. PSNR and SSIM ratio showed a constant image quality over all the array spacing. The number of array elements was increased and linear operation like averaging was applied. The results showed no improvement in the gain and image quality. ii To overcome the problem of correlation sidelobes, a non-linear combining process has been proposed. Using the non-linear combining process it was found that the SNR showed an average gain of 10 dB on simulated data over the images formed without it. The PSNR and SSIM also showed a small increase in the image quality. The computational complexity of the proposed non-linear combining process was calculated by determining the number of multiplications and additions. The time taken to perform these operations on a SHARC ADSP 21261 chip was calculated theoretically. The calculations showed the feasibility of using this algorithm on a digital signal processing (DSP) hardware. An experimental prototype was built and performance was tested during sea trials. The data obtained was processed using a computer. The experimental results verified that the processing algorithm was effective in a practical system. |
Description: | PhD Thesis |
URI: | http://hdl.handle.net/10443/1220 |
Appears in Collections: | School of Electrical, Electronic and Computer Engineering |
Files in This Item:
File | Description | Size | Format | |
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Menon11.pdf | Thesis | 6.67 MB | Adobe PDF | View/Open |
dspacelicence.pdf | Licence | 43.82 kB | Adobe PDF | View/Open |
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