Inspired by promotion of commercial applications, support of location-based services to mobile terminals through their current location has been receiving a lot of attention in recent years even though emergency communications is the primary motivation for development of wireless location. A major challenge to wireless location technique is how to balance the implementation complexity and required accuracy. In the first part of this dissertation, we address one of the fundamental problems in wireless location when using the ToA measurements and develop a simple model to estimate the mobile terminal location with low complexity and promising accuracy. The model employs the geometrical transformation method with single propagation delay measurement. The contribution is that the use of geometrical transformation allows us to overcome the location handover problem, i.e., a forcing handover in a GSM (global system for mobile) network or a three-way soft handover in a UMTS (universal mobile telecommunications system) network. By using the proposed location model, the impact on network performance is kept at the minimum level and the complexity and requirements for hardware and software changes are reduced. In the second part of this dissertation, we address one of the fundamental problems in wireless location when using the SS (signal strength) measurements. The first contribution is to develop a novel wireless location technique based on a ¡§differ- encing¡¨ way, called the SSSD (stationary signal-strength-difference), to remove the uncertainty propagation parameters when merging environment-dependent signal propagation model into the location estimation. This is due to the uncertainty in propagation parameters causes a propagation model error that enlarges error in the distance estimation. The performance gained from the preliminary analysis of SSSD location technique, however, is degraded as a result of the large bias error in the estimated distance and distance difference. To achieve the performance enhancement, the second contribution is to correct the bias error in the estimated distance difference by using a correction method based on a geometric constraint condition. With the corrected distance difference, the final contribution is that we generalized the work on correction method and provide a new framework to correct the error in the estimated distance. As the corrected distance and distance difference is derived by LS (least square) computation, respectively, low computation burden and non-iterative solutions were achieved. To the best of our knowledge thus far, this is first such proposal for a correction to the SS-based location technique. It is demonstrated that the proposed error correction method is shown to perform well when encountering the large error in the estimated distance and distance difference, and prove that the location accuracy can be improved considerably.

The aim of this thesis is to determine whether surface electromyography (EMG) can be used as a diagnostic tool in chiropractic practice to identify the functional status of the lumbar paraspinal muscles. There were two main studies to achieve this aim. The reliability and validity of the surface EMG signal to measure the activity of paraspinal muscles during maintenance of simple static postures was evaluated. During maintenance of static postures, the raw surface EMG signal was often contaminated by an electrocardiographic (ECG) signal. Although the ECG artefact was successfully removed using two different ECG removal techniques (manual and semi-automatic), the reliability of the surface EMG signal was not significantly improved (ICC less than 0.75) for both non-normalised and normalised data. Therefore the static postures that were used in this thesis did not provide a protocol that can be used to measure the functional status of the lumbar paraspinal muscles in clinical practice. However, when muscle contraction was at a moderate level, the reliability of EMG signal became better. Walking was considered to be a possible protocol to record a reliable surface EMG signal from paraspinal muscles. Three components of the surface EMG signal were used to characterise the pattern of muscle activity during steady state walking. The narrow window technique was used to characterise the peak activation point of the activity envelope in order to capture a stationary signal from which to calculate amplitude and frequency measures. Walking is a cyclic activity. The back muscles contract rhythmically during a single gait cycle. It is possible to identify the start and end points of the activity envelope associated with the rhythmic contraction of the muscles and define the timing of the muscle activation cycle relative to heel strike. The metronome was found to be useful to control the pace of natural walking in this study. The surface EMG signal of the first recording minute (1 ~ 2 minute) was not associated with a signal that was stable in terms of the parameters that were used in this study. It wa s found that the last recording minute (9 ~ 10 minute) can be used. This suggests that it may be necessary for subjects to walk for a defined period lasting some minutes before the commencement of recording of the surface EMG. Surface EMG may be used as a tool to measure activation patterns of the low back muscles during muscle contraction associated with the support of various static postures or during the execution of dynamic movements such as walking in the real world. The static postures used in this thesis to record the surface EMG signal from the lumbar paraspinal muscles were found not to provide the basis for a reliable and valid tool. However, a walking exercise might be an alternative activity which can be used easily in clinical practice. The components of the surface EMG signal that may be used in future studies might include measures of the amplitude, frequency and timing of the surface EMG signal.

The radar transmitter identification problem involves the identification of a specific radar transmitter based on a received pulse. The radar transmitters are of identical make and model. This makes the problem challenging since the differences between radars of identical make and model will be solely due to component tolerances and variation. Radar pulses also vary in time and frequency which means that the problem is non-stationary. Because of this fact, time-frequency representations such as shift-invariant quadratic time-frequency representations (Cohen’s class) and wavelets were used. A model for a radar transmitter was developed. This consisted of an analytical solution to a pulse-forming network and a linear model of an oscillator. Three signal classification algorithms were developed. A signal classifier was developed that used a radially Gaussian Cohen’s class transform. This time-frequency representation was refined to increase the classification accuracy. The classification was performed with a support vector machine classifier. The second signal classifier used a wavelet packet transform to calculate the feature values. The classification was performed using a support vector machine. The third signal classifier also used the wavelet packet transform to calculate the feature values but used a Universum type classifier for classification. This classifier uses signals from the same domain to increase the classification accuracy. The classifiers were compared against each other on a cubic and exponential chirp test problem and the radar transmitter model. The classifier based on the Cohen’s class transform achieved the best classification accuracy. The classifier based on the wavelet packet transform achieved excellent results on an Electroencephalography (EEG) test dataset. The complexity of the wavelet packet classifier is significantly lower than the Cohen’s class classifier. Copyright / Dissertation (MEng)--University of Pretoria, 2010. / Electrical, Electronic and Computer Engineering / unrestricted

The doctoral thesis focuses on a Vold-Kalman filter (VKF). Theoretical part describes properties of VKF and other order tracking methods, namely computed order tracking (COT) and Gabor order tracking (GOT). It also characterizes requirements for rotational speed measurements as one of the key elements for correct functionality of VKF. Practical part depicts own filter implementation and its properties. Main stress is put on computational efficiency, that is in result better than in available codes. Thesis also points out possible issues with numerical instabilities within calculation caused by limited dynamic range of double data type. This is solved by restricting the inputs to prevent the instabilities. Restriction is applied also to cases where the result is numerically correct but unusable. Following part extends the comparison with methods STFT, COT and GOT, where benefits of VKF for nonstationary conditions are shown. The last section shows given information used on simulated signals. This is then applied to show mentioned techniques on experimental data, for instance from turbo engine or electric motor, where the ability of VKF in checking the accordance between speed profile and vibration data is illustrated.