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|Title:||Techniques for Identifying Search and Rescue Satellite Aided Tracking (SARSAT) Signals|
|Authors:||El-Naga, Mohamed Abou Samia|
|Department:||Electrical and Computer Engineering|
|Keywords:||Electrical and Computer Engineering;Electrical and Computer Engineering|
|Abstract:||<p>This dissertation studies the problem of identification of the emergency locator transmitter (ELT) signals as related to the Search and Rescue Satellite Aided Tracking (SARSAT) system. The ELT identification is particularly important in order to increase the probability of detection and eliminate sources of interference from the data set.</p> <p>A set of parameters that uniquely characterizes the ELT signals is selected, namely, the width of the average spectrum sidebands, the ratio of the sideband plateaus of the average spectrum with respect to the carrier peak and the sweep period of the signals. Two methods for estimating the sweep period are developed theoretically. These are the sawtooth and the crosscorrelation methods.</p> <p>The identification techniques are tested using computer generated signals and real testbed ELT signals recorded by the Communications Research Centre (CRC) in Ottawa.</p> <p>A study of the different interference sources in the 121.5/243 MHz SARSAT frequency bands is provided. Three different sources of interference are generated and tested using the identification techniques.</p> <p>The performance of the proposed techniques is further investigated using real data from two different passes of COSPAS satellite CI.</p> <p>Using the identification techniques presented in this thesis, it is possible to consolidate the number of detections per day from multiple satellites and multiple satellite passes.</p>|
|Appears in Collections:||Open Access Dissertations and Theses|
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