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This thesis deals with the development of automatic methods for nding pulsation events in time series produced by the radars in the SuperDARN network. These methods are then applied to the detection and analysis of pulsation events illustrating the relative usefulness of radar data for the study of global pulsation dynamics. Each of the SuperDARN radars produces 1200 Doppler velocity records every hour. If backscatter is present, and there is a pulsation occurring in the same region as the scatter, the pulsation can be measured as periodic changes in the Doppler velocity of that record. There are over 85 million Doppler velocity data records for 2004. In order to identify pulsations in these data, an automated pulsation nder was developed. All records with signi cant peaks in the FFT spectra were tagged as having a pulsation present. If a record had less than 20% data missing it was termed a clean record as it was suitable for use with the automated pulsation nder. As pulsations can only be observed if there are scatter, an investigation into scatter characteristics are presented. It is shown that the occurrence of clean records is most strongly in uenced by IMF Bz, and the underlying spatial structure of the SuperDARN network. The results for the automated pulsation nder for 2004 are then presented. It was found that the average daily distribution of pulsation events, shown as a function of pulsation frequency, followed 1/f distribution with no distinct peaks. It was also found, however, that the standard deviation of the average showed peaks close to the "magic" frequencies indicating that on average there is more variation at these frequencies that any of the other pulsation frequencies measured. The occurrence of pulsations followed the clean scatter statistics both temporally and directionally telling us that the network is not suited for studying global pulsation dynamics because the variations in scatter dominated any variations in pulsation occurrence. Data from a few events identi ed by the pulsation nder are then presented to illustrate the advantages and disadvantages of using SuperDARN data for pulsation event studies. The events show a pulsation that occurs at its fundamental and third harmonics, an aliased pulsation, a pulsation, interrupted by sounding frequency changes, that shows how ionospheric scatter was tagged as ground scatter and how data from two overlapping pulsations in di erent radars can be merged to give the poloidal and toroidal characteristics of the event. / Thesis (Ph.D.)-University of KwaZulu-Natal, Westville, 2009.

The Kalman filter algorithm can be applied as a recursive estimator of the state of a dynamic system described by a linear difference equation. Given discrete measurements linearly related to the state of the system, but corrupted by white Gaussian noise, the Kalman filter estimate of the system is statistically optimal with respect to a quadratic function of the estimate error. The first objective of this paper is to give deep enough insight into the mathematics of the Kalman filter algorithm to be able to choose the correct type of algorithm and to set all the parameters correctly in a basic application. This description also includes several examples of different approaches to derive and to explain the Kalman filter algorithm. In addition to the mathematical description of the Kalman filter algorithm this paper also provides an implementation written in MATLAB. The objective of this part is to correctly replicate the target tracker used in the surveillance radar PS-90. The result of the implementation is evaluated using a simulated target programmed to have an aircraft-like behaviour and done without access to the actual source code of the tracker in the PS-90 radar

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