The main purpose of a radar is to detect, recognize, and track objects of interest. When it is known that only a single target is present, the matched filter is proven to be optimal detector. However, in practice, a radar scene often consists of multiple targets. For example, in air surveillance and monitoring applications, multiple aircrafts might be in the airspace. When multiple targets are to be detected the matched filter is not guaranteed to give the best results. This can happen when a strong reflector masks the signals reflected from weak reflectors, thereby resulting in missed detections. Furthermore, when the sensor resolution is low, targets that are spaced closely together may only result in a single target actually being detected. This research explores how the Relevance Vector Machine (RVM) framework may be used to achieve a better multi-target detector than the commonly used basic matched filter approach. RVM was selected to resolve the multi-target detection problem as it estimates the target locations iteratively. In this research it was shown how the RVM framework can be used to model the fluctuation of swerling I/II targets. Additionally, the RVM algorithm was modified to incorporate a notion of statistical thresholding. Simulations show that using RVM the false alarm rate can be reduced and target locations can be more accurately recovered compared to other existing methods in case of multiple swerling I/II fluctuating targets. Furthermore, the proposed approach is shown to have a much lower convergence time compared to a similar expectation-maximization based method, namely Enhanced Sparse Bayesian Learning.

Solar energy is being increasingly used in many sectors as it is clean energy which requires minimum operation and maintenance costs [1]. One of the potential _elds of applications of solar energy is the aviation industry, speci_cally in small aircraft and monitoring devices. Many research projects have been conducted in developing solar energy based aircrafts, like Helios and Solar Impulse [2][3]. The total energy that can be harnessed by using solar panels in the aircraft may not alone be su_cient to provide enough power required for the aircraft due to several reasons including additional weights of components (battery, converter) and requirements of large surface area [4][5]. Therefore, one of the attractive options is to use solar technology as an additional source of energy for extending the ight time or range of an aircraft. PV technology o_ers the ability to provide an uninterrupted longer term power supply as energy can be continuously harvested during ight and stored for later use. This extension possibility of ight time has become increasingly important in various _elds such as environmental monitoring and military applications in manned and unmanned aircrafts. This BSc thesis is a part of the `Solar Plane` bachelor graduation project. The main goal of the project was to extend the ight time of a small commercially available aircraft using photovoltaic (PV) technology. The project was split into 3 sub-groups: PV (Photovoltaic), power electronics (PE) and control. This thesis describes the design and implementation of the PV system/layout and the software used for maximum power point tracking (MPPT).