Signal Correlation is a digital signal processing technique which has a wide variety of applications, ranging from geophysical exploration to acoustic signal enhancements, or beamforming. This dissertation will consider this technique in an underwater acoustics perspective, but the algorithms illustrated here can be readily applied to other areas. Although beamforming techniques have been studied for the past fifty years, modern beamforming systems still have difficulty in operating in noisy environments, especially in shallow water.

In the last decade, 802.11 wireless devices data-rates have increased by three orders of magnitude, while communications experiencing low throughput are still largely present. Such throughput loss is a fundamental problem of wireless networking that is difficult to diagnose and amend. My research addresses two key causes of throughput loss: MAC layer protocol overhead and destructive link interference. First, I design WiFi-Nano reducing the channel access overhead by an order of magnitude leveraging an innovative speculative technique to transmit preambles. This new concept is based on simultaneous preamble transmission and detection via a self-interference cancellation design, and paves the way to the realization of the collision detection paradigm in wireless networks. Next, I propose 802.11ec (Encoded Control), the first 802.11-based protocol that eliminates the overhead of control packets. Instead, 802.11ec coordinates node transmissions via a set of predefined pseudo-noise codewords, resulting in the dramatic increase of throughput and communication robustness. Finally, I design MIDAS, a model-driven network management tool that alleviates low throughput wireless links identifying key corrective actions. MIDAS' key contribution is to reveal the fundamental role of node transmission coordination in characterizing destructive interference. I implement WiFi-Nano, 802.11ec, and MIDAS using a combination of WARP FPGA-based radio boards, custom emulation platforms, and network simulators. The results obtained show that WiFi-Nano increases the network throughput by up to 100%, 802.11ec improves network access fairness by up to 90%, and MIDAS identifies corrective actions with a prediction error as low as 20%.

This thesis deals with design and realization of acoustic camera for sound source location. The essence of the device is microphone field listening for acoustic impulses which are processed in real-time in order to locate the source. Found location is displayed on LCD together with images from regular video camera. FPGA is used as a computational unit.

This master’s thesis deals with flame detection methods. The purpose of the project was to create a flame detector, which uses the alternative method of flame detection. The introduction of this thesis gives the summary overview of the existing methods for flame detection. Further, the existing flame detectors and their applications are described. Two alternative algorithms for flame detection which are based on the digital signal analysis were realized on the PC. Flame detector, which utilizes the digital analysis of audio signal, was realized on 8 bit microcontroller Atmega128 and achieved results are presented.

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