Fuentes, Abigail

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    Dft beamforming techniques for bioacoustics signal processing applications
    (2009) Fuentes, Abigail; Rodríguez, Domingo; College of Engineering; Rodríguez, Néstor J.; Santiago, Nayda; Department of Electrical and Computer Engineering; Quintana, Julio
    This work presents a computational framework for the analysis, design, and development of discrete Fourier transform (DFT) beamforming techniques for bioacoustics signal processing applications. DFT beamforming techniques are a form of hierarchical beamforming algorithm methods which deal with the processing of signals arriving at large aperture array systems. The processing of the sensored signals is conducted hierarchically in the frequency domain.The DFT beamforming algoritms consist of determining the direction of arrival (DOA) of plane waves impinging on a linear sensor array. One of the applications of the sensors is as signal instrumentation resources for monitoring and surveillance of neo-tropical anurans in the island of Puerto Rico, in a near real time manner. A plane wave complex signal model is being utilized to model the incoming signals which are spatially sampled by the array elements and temporally sampled by the sensor signal acquisition system. The DFT beamforming algorithms are being formulated using Kronecker products algebra to provide general expressions for the beamforming operations. The development e??ort is being conducted using the MATLAB numeric computation and software visualization package. A parallel programming modeling environment, named pMATLAB, is being utilized to study the computational performance of parallel implementation techniques. Preliminary implementation e??orts have being conducted using C language on the TMS320C6713 Digital Signal Processing (DSP) unit from Texas Instruments. A wireless sensor array processing (SAP) system has also been designed at the Automated Information Processing (AIP) Laboratory, at the University of Puerto Rico, Mayaguez Campus, with the purpose of providing further testing of the beamforming techniques developed. Such SAP testbed uses Linux-based embedded small computers , called Gumstix, as sensor signal processing nodes (SSP), with the capacity to acquire, store, and process acoustic data. A principal node, called the Master Sensor Node (MSN) receives the processed data from the SSP nodes, making the data available via wireless connection to the Internet. This type of network system will serve as an ideal tool for biologists to monitor, locate, and track species of interests in the surrounding environments, without interfering with the ecological system, and avoiding frequent ??eld visits.