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In this paper, a channel measurement campaign done with the system from the University of Kassel, will be investigated. With very high bandwidth (600 MHz), a large room has been measured at 1.8 GHz with a moving antenna, forming a synthetic aperture. Afterwards, the transformation from the transfer function in the frequency-domain to the time-domain received signal, with the training sequence included, will be explained. On these data, the Space Alternating Generalised Expectation maximisation (SAGE) Algorithm will be applied to extract with high resolution the Direction of Arrival (DOA) parameters, in this case the time delay, the azimuth angle and the complex amplitude for every significant path. The extraction results will be evaluated and visually interpreted

TTiis paper describes a toolbox tor the application in the field of 'Spectral Analysis & Linear Prediction' that can be used with MATLAB 0 . This tool collection has been developed, implemented and utilized by the department of RF-Techniques/Communicatbn Systems at the University of Kassel in context with analyzing and predicting the mobile radio channel. The toolbox as well as a brief installation and reference guide is available for download from the department of RF-Techniques/Communication Systems homepage.

In this paper the problem of extracting signal parameters of stationary and non-stationary signals by applying a parameter estimation scheme is discussed. At first, a Maximum Likelihood based approach is introduced, which combines the most classical spectral analysis tool, the Fourier transform, with a modern parameter estimation scheme, the EM algorithm. After explaining the ideas of local polynomial approximation, an extended signal model is proposed, which considers linear parameter variations in order to extract the evolutional characteristics of a non-stationary signal. By replacing the EM algorithm with its extended derivative the SAGE algorithm, an efficient method for extracting the parameters of superimposed chirp signals is derived. The performance of the novel algorithm is illustrated on the basis of a synthetic test signal. Furthermore, an application to the problem of extracting time-varying parameters of a frequency selective radio channel is presented to show the flexibility of the proposed estimation scheme. Übersicht Dieser Beitrag behandelt das Problem der Parameterschätzung von stationären und nicht-stationären Signalen. Es wird ein Maximum-LJkelihood-Ansatz vorgestellt, welcher die klassische Fourier-basierte Spektralanalyse mit einem modernen Parameterschätzverfahren, dem EM-Algorithmus, kombiniert. In Erweiterung dieses Verfahrens wird ein Signalmodell vorgeschlagen, welches lineare Variationen der Signalparameter und somit die zeitveränderlichen Eigenschaften eines nicht-stationären Signals berücksichtigt. In Verbindung mit dem gegenüber dem EM-Verfahren erweiterten SAGE-Algorithmus wird ein effizientes Verfahren zur Extraktion der Parameter überlagerter Chirp-Signale abgeleitet. Die Leistungsfähigkeit wird anhand eines synthetischen Testsignals dargestellt und diskutiert. Darüber hinaus erfolgt beispielhaft eine Anwendung des Verfahrens auf die Problemstellung der Parameterschätzung eines Zeitvarianten und frequenzselektiven Mobilfunkkanals, um die Flexibilität des vorgeschlagenen Parameterschätzverfahrens zu demonstrieren. Für die Dokumentation Parameterschätzung nicht-stationärer Signale / Chirp-Parameterextraktion / Funkkanal-Parameterschätzung / SAGE-Algorithmus