This thesis investigates the improvements that can be made to Bayesian passive sonar tracking in the context of active-passive sonar data fusion. Performance improvements are achieved by exploiting the prior information available within a typical Bayesian data fusion framework. The algorithms developed are tested against both simulated data and data measured during the SEABAR 07 sea trial. Results show that the proposed approaches achieve improved detection, decreased estimation error, and the ability to track quiet targets in the presence of loud interferers. / text

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There are many Sciaenid species found in coastal water of Taiwan, and most of them can generate sound in the spawning season. However due to overfishing, the populations of these high economic value fishes have been greatly decreased. To study and protect Sciaenid, whose habitat should be identified to set up seasonal protection zones. In this study, easy and low cost measure by using passive sonar is proposed to map the habitat in the field. Measurement and analysis of Sciaenid¡¦s sound were performed to investigate its acoustic characteristic, and frequency range was found to be 350 to 1,500 Hz. The statistical distribution of sound levels can be built up by enough field measurement, therefore source levels can be defined in this method. In the addition, the transmission loss of in site shallow water was studied to compute the real decaying factor (TL=n*logR) of the survey site. By using 3 sonobuoys, with known source level distribution and transmission loss, the distance of possible habitat can then be inverted. Through enough measurements, the map of coastal habitat of Sciaenid can be generated with efficiency and accuracy.

Abstract Sciaenids are a kind of economic oceanic fish with the most dynamic vocal activity. It is important to find out what type of sound a soniferous fish can make. Therefore, I used this acoustic character as a tool to study the distribution of sciaenids in order to manage their fisheries. In the previous researches, scientist found that there were eight types of sounds (A~H type) appearing on the coastal areas of Yunlin, and the frequency range of the H-type sound could reach to 8000Hz. This sound was suspected to be made by Otolithes ruber. Connaughton (1994) and Sprague (2000) mentioned that the differences of length, weight, and tension of the sonic muscle and the amount of protein and glycogen affect the types of sounds emitted. To reveal the producer of high-frequency sound, this research analyzed and compared the length, width, thickness and somatic of sonic muscle and the amount of protein and glycogen in seven sciaenid species occuring on the west coast of Taiwan (Johnius tingi, Johnius sina, Johnius amblycephalus, Johnius amblycephalus, Pennahia argentata, Chrysochir aureus, and Otolithes ruber), then to find if the differences of physic parameter and energy supplication are the major factors making O. ruber produce high frequency of sound. In this research, I found that the length of O. ruber¡¦s sonic muscle was shorter than that other of sciaenids. However the weight of sonic muscle did not significantly differ although it was still the lightest one (2.33¡Ó1.00g). The amount of protein (20.37¡Ó0.67¢M) and glycogen (0.33¡Ó0.11¢M) in O. ruber was higher than that of other species and the cross section of sonic muscle fiber was smaller. These characteristics are suitable for O. ruber to make a high-frequency sound. Because of the sound is believed to be made by rubber, so passive sonar was applied to investigate the distribution of this sound type on the estuaries along the west coast of Taiwan (Tam-Shui River, Tou-Chien River, Ta-Chia River, Cho-sui River, Zeng-Wen River, and Kao-Ping River) to represent distribution of O. ruber and its seasonal change of vocal activity. Acoustic activity reached it peak in spring then decreased through summer, autumn, and winter. More sounds were found in the estuaries south of the Cho-sui River (including Cho-sui, Zeng-Wen, and Kao-Ping River) than those north of this river (including Ta-Chia, Tou-Chien, and Tam-Shui River).

This work investigates the ideal distribution of sensors in networked arrays. MATLAB models these arrays and simulates the results these networks obtain using active and passive sonar. These results determine the ideal sensor placement for optimal parameter detection and estimation of targets. This work's first part focuses on active sonar networks with a fixed number of sensors in a differing number of arrays. MATLAB simulates the data of these sensors taking into account the geometries and velocities of the arrays and targets, then estimates the parameters of the targets using an elliptical filter, a conventional beamformer, a matched filter and one of three fusion methods. This work compares the performance of each network and fusion method. This work shows that the adding more arrays, regardless of size, enhances the overall performance of the network. It also shows the larger arrays obtain more robust parameter estimation. The second part of this work investigates the effects of uncertainty of the array position and orientation using passive sonar. Two networks, one with 2 32-channel arrays and one with 8 2-channel arrays, estimate a sound source's location using a conventional beamformer. MATLAB simulates the data taking into account the geometries of the arrays and the sound source. The results of these simulations show that when uncertainty of position and orientation increases, the better the smaller arrays estimate the location of the sound source compared to the larger arrays. / Master of Science

Since World War I, the area of acoustic undersea warfare has witnessed several research activities targeting the development of advanced systems to accurately detect and localize underwater moving targets. One of the main categories of these systems is the passive sound navigation and ranging (SONAR) that searches for the location of the ships and submarines by listening to the radiated noise produced by their propellers, machinery, and flow dynamics. The performance of the passive sonar highly depends on the particular array signal processing algorithms used in practice. Presently, one of the main challenges is to accurately estimate the target direction of arrival (DOA) in severe underwater environments. This thesis is proposed to enhance the DOA estimation in two distinct applications. This first application is to improve the spatial resolution of the uniform linear towed arrays. This is done by applying new spatial extrapolation techniques called 2D- and 3D- fast orthogonal search (FOS) for both uniform linear and rectangular arrays, respectively. The presented methods show better performance than the conventional methods with respect to signal to noise ratio (SNR), number of snapshots and angular separation. Moreover it reduces the computational complexity required by the spatial extrapolation methods based on linear prediction approach. The other application concerns with developing a new DOA estimation that provides better spatial spectrum than the one provided by conventional beamforming (CBF) when a nonuniform linear array of directional frequency analysis and recording (DIFAR) sonobuoys is employed. The introduced technique or the so called fourth order cumulant beamforming (FOCBF) and shows an outstanding performance compared to CBF especially in low SNR. Furthermore, a warping FOC-BF (WFOC-BF) method obtained by augmenting a warping beamforming technique with FOC-BF is proposed to reduce the required computational complexity by FOC-BF while preserving the same performance. / Thesis (Ph.D, Electrical & Computer Engineering) -- Queen's University, 2012-06-27 14:59:33.941