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|Title:||Fundamental Analysis for the Processing of Search and Rescue Satellite-Aided Tracking (SARSAT) Signals at Baseband|
|Authors:||Dessouky, Ibrahiem Moawad Moawad|
|Department:||Electrical and Computer Engineering|
|Keywords:||Electrical and Computer Engineering;Electrical and Computer Engineering|
|Abstract:||<p>Search and rescue satellite aided tracking (SARSAT) is a method of employing satellites in low polar orbits to relay the emergency signals of distressed aircraft and marine vessels to an earth station. At the earth station, the signals are processed using spectral estimation techniques which permit the calculation of the location of the distressed vehicle. Of considerable importance are the characteristics of the spectrum of the emergency locator transmitter (ELT) signal since the probability of locating the downed aircraft is closely related to the quality of the ELT signal itself.</p> <p>This thesis analyses and investigates the ELT signal spectra for ranges of different parameter values. A mathematical representation for the variation of the pulse duration across the sweep period for actual real ELT signals has been developed and verified. New models are proposed with nearly ideal spectral properties.</p> <p>The matched filter performance for detection of the ELT signals has been calculated. Also, the periodogram and averaged periodogram performances for detection of the ELT signals are calculated and verified by computer simulation.</p> <p>A new processor, called the complex baseband processor, which employs both the periodogram and the maximum entropy method (MEM) is developed. Baseband processing has many advantages over bandpass processing.</p> <p>This thesis examines the processing of simulated ELT signals, real testbed ELT signals and actual data received from satellite passes using this new baseband processor. It is shown theoretically and by computer simulation that the minimum detectable carrier-to-noise density ratio (CNDR) is approximately 21 dB-Hz when the 512 complex-point FFT is applied to 50 blocks comprising 1 second of data.</p> <p>A new technique called rate reduction filtering is developed. By applying this technique to the data sequence, improved frequency resolution is obtained along with an increase in signal-to-noise ratio. Further, a new algorithm called "ELT Tracking Algorithm" based on using rate reduction filtering is developed and analysed.</p>|
|Appears in Collections:||Open Access Dissertations and Theses|
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