<p>Solid-state LED lighting is a promising technology to improve the energy efficiency of general illumination. The inherent modulation bandwidth of these devices can be exploited to provide a dual role as a communication device. This method of communication is termed visible light communications (VLC).</p> <p>Due to dispersive nature of the VLC channel, orthogonal frequency division multiplexing (OFDM) has been proposed to allow multi-user communication while mitigating the effects of inter-symbol interference (ISI). However, OFDM is in general not compatible with intensity modulation and direct detection (IM/DD) channels since it has both positive and negative amplitudes. Various techniques have been proposed that provide compatible optical OFDM signaling such as DC-biased OFDM, asymmetrically clipped optical OFDM (ACO-OFDM), and pulse amplitude modulated discrete multi-tone (PAM-DMT).</p> <p>This thesis develops spectrally factorized optical OFDM (SFO-OFDM) as a framework to implement OFDM on optical intensity channels. The drawbacks of conventional methods are mitigated in SFO-OFDM. Contrary to ACO-OFDM and PAM-DMT, the proposed technique uses all the available bandwidth for data modulation and does not require reserved subcarriers. Simulation results verify that SFO-OFDM has gain both in optical power efficiency and peak-to-average power ratio compared to conventional optical OFDM schemes.</p> <p>Furthermore in this thesis, a new receiver design for ACO-OFDM and PAM-DMT is proposed. Unlike conventional receivers that ignore the structure of the transmitted signal, the new detector exploits this structure to improve the optical power efficiency. By observing the time domain samples, a simple pairwise maximum likelihood detector is developed and used to remove half of the noise power. It is also shown by simulation results that employing the proposed detector design leads to a significant gain in optical power efficiency.</p> / Master of Applied Science (MASc)

Since its discovery, in the 1940's, radar (Radio Detection and Ranging) has become an important ranging sensor in many areas of technology and science. Most of the military and many civilian applications are unimaginable today without radar. With technology development, radar application areas have become larger and more available. One of these applications is Synthetic Aperture Radar (SAR), where an airborne radar is used to create high resolution images of the imaged scene. Although known since the 1950's, the SAR methods have been continuously developed and improved and new algorithms enabling real-time applications have emerged lately. Together with making the hardware components smaller and lighter, SAR has become an interesting sensor to be mounted on smaller unmanned aerial vehicles (UAV's). One important thing needed in the SAR algorithms is the estimate of the platform's motion, like position and velocity. Since this estimate is always corrupted with errors, particularly if lower grade navigation system, common in UAV applications, is used, the SAR images will be distorted. One of the most frequently appearing distortions caused by the unknown platform's motion is the image defocus. The process of correcting the image focus is called auto-focusing in SAR terminology. Traditionally, this problem was solved by methods that discard the platform's motion information, mostly due to the off-line processing approach, i.e. the images were created after the flight. Since the image (de)focus and the motion of the platform are related to each other, it is possible to utilise the information from the SAR images as a sensor and improve the estimate of the platform's motion. The auto-focusing problem can be cast as a sensor fusion problem. Sensor fusion is the process of fusing information from different sensors, in order to obtain best possible estimate of the states. Here, the information from sensors measuring platform's motion, mainly accelerometers, will be fused together with the information from the SAR images to estimate the motion of the flying platform. Two different methods based on this approach are tested on the simulated SAR data and the results are evaluated. One method is based on an optimisation based formulation of the sensor fusion problem, leading to batch processing, while the other method is based on the sequential processing of the radar data, leading to a filtering approach. The obtained results are promising for both methods and the obtained performance is comparable with the performance of a high precision navigation aid, such as Global Positioning System (GPS). / LINK-SIC

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International Telemetering Conference Proceedings / October 26-29, 1992 / Town and Country Hotel and Convention Center, San Diego, California / Our telemetry department has an application for a data categorization/compression of a high speed transient signal in a short period of time. Categorization of the signal reveals important system performance and compression is required because of the terminal nature of our telemetry testing. Until recently, the hardware for the system of this type did not exist. A new exploratory device from Intel has the capability to meet these extreme requirements. This integrated circuit is an analog neural network capable of performing 2 billion connections per second. The two main advantages of this chip over traditional hardware are the obvious computation speed of the device and the ability to compute a three layer feed-forward neural network classifier. The initial investigative development work using the Intel chip has been completed. The results from this proof of concept will show data categorization/compression performed on the neural network integrated circuit in real time. We will propose a preliminary design for a transient measurement system employing the Intel integrated circuit.

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published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

published_or_final_version / abstract / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

Graduate