The use of underwater systems has grown significantly, and they can be used both for military and civilian purposes. Many of their parts are replaceable. An underwater vehicle can be equipped with different devices depending on the taskit should carry out. This can make the vehicle unbalanced, which means that the demand for balancing systems will increase in line with the increasing use of underwater systems. The goal of the thesis is to deliver a method for balancing based on parameters estimated both in static and dynamic operation. The parameters define a nonlinear physical model that can describe the underwater vehicle in different environments and conditions. The main idea in the proposed method for parameter estimation based on static operation data is to solve equilibrium equations when the on-board control system is used to maintain two different orientations. The balancing can then be done by solving an optimisation problem that gives information about where additional weights or float material should be installed. The static parameter estimation has been evaluated successfully in simulations together with three ways of solving the balancing problem. The dynamic parameter estimation has also been evaluated in simulations. In this case, the estimated parameters seem to have the same sign as the true ones but it seems difficult to obtain accurate estimates of some of the parameters. However, the total dynamic model was good except the prediction of the vertical movements. In particular, the model could explain the rotations of the vehicle well. The reason for the worse performance for the vertical movements might be some difficulties when generating suitable excitation signals. The work done by Feras Faez Elias in connection to this master thesis made a contribution to a patent application that Saab AB has filed where Feras Faez Elias was one of the inventors.

In high range-resolution (HRR) radar systems, the returns from a single target may fall in multiple adjacent range bins which individually vary in amplitude. A target following this representation is commonly referred to as an extended target and results in more information about the target. However, extracting this information from the radar returns is challenging due to several complexities. These complexities include the single dimensional nature of the radar measurements, complexities associated with the scattering of electromagnetic waves, and complex environments in which radar systems are required to operate. There are several applications of HRR radar systems which extract target information with varying levels of success. A commonly used application is that of imaging referred to as synthetic aperture radar (SAR) and inverse SAR (ISAR) imaging. These techniques combine multiple single dimension measurements in order to obtain a single two dimensional image. These techniques rely on rotational motion between the target and the radar occurring during the collection of the single dimension measurements. In the case of ISAR, the radar is stationary while motion is induced by the target. There are several difficulties associated with the unknown motion of the target when standard Doppler processing techniques are used to synthesise ISAR images. In this dissertation, a non-standard Dop-pler approach, based on Bayesian inference techniques, was considered to address the difficulties. The target and observations were modelled with a non-linear state space model. Several different Bayesian techniques were implemented to infer the hidden states of the model, which coincide with the unknown characteristics of the target. A simulation platform was designed in order to analyse the performance of the implemented techniques. The implemented techniques were capable of successfully tracking a randomly generated target in a controlled environment. The influence of varying several parameters, related to the characteristics of the target and the implemented techniques, was explored. Finally, a comparison was made between standard Doppler processing and the Bayesian methods proposed. / Dissertation (MEng)--University of Pretoria, 2013. / gm2014 / Electrical, Electronic and Computer Engineering / unrestricted