We consider the problem of narrow-band signal detection in a passive sonar environment. The collected signals are passed to a fast Fourier Transform (FFT) delay-sum beamformer. In classical signal detection, the output of the FFT spectrum analyser in each frequency bin is the signal power spectrum which is used as the signal feature for detection. The observed signal power is compared to a locally estimated mean noise power and a log likelihood ratio test (LLRT) can then be established. In this thesis, we propose the use of the power spectral density (PSD) matrix of the spectrum analyser output as the feature for detection due to the additional cross-correlation information contained in such matrices. However, PSD matrices are structurally constrained and therefore form a manifold in the signal space. Thus, to find the distance between two matrices, the measurement must be carried out using Riemannian distance (RD) along the tangent of the manifold, instead of using the common Euclidean distance (ED). In this thesis, we develop methods for measuring the Frechet mean of noise PSD matrices using the RD and weighted RD. Further, we develop an optimum weighting matrix for use in signal detection by RD so as to further enhance the detection performance. These concepts and properties are then used to develop a decision rule for the detection of narrow-band sonar signals using PSD matrices. The results yielded by the new detection method are very encouraging. / Thesis / Master of Applied Science (MASc)

Thesis (M.S. in Modeling, Virtual Environments and Simulation (MOVES))--Naval Postgraduate School, March 2004. / Thesis advisor(s): Christian Darken, Curtis Blais. Includes bibliographical references (p. 103-104). Also available online.

<p> In the past, analog circuits, discrete digital logic circuits or minicomputers have been used to implement the signal processing section of a sonar systems. More recently, microprocessor based logic circuit designs have produced a new breed of system design approach which gives designers the flexibility that has never been available through the use of analog or discrete logic circuits; however, due to the inherent slow speed of the metal-oxide semiconductor (MOS) logic circuits, incorporating microprocessors in the implementation of a sonar signal processor is not feasible. With the advent of bipolar Schottky large scale integrated circuit technology, the speed performance of the microprocessors have been improved considerably, and signal processor designs employing microprocessors are now feasible. </p> <p> The main objective of this work is to design, implement, and test a real-time digital sonar signal processor for processing pulsed CW signals. With design based on the use of the bit slice microprocessor, a signal processor has been constructed that has an 8 bit input, a 16 bit output. The processor is capable of detecting 16 different Doppler shifts. Laboratory generated signals are used in the testing and the experimental results show good agreement with the theory. A possible means of expanding the existing single channel signal processor into a multichannel processor has also been outlined. </p> / Thesis / Master of Engineering (MEngr)