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Detecting Chaotic Signals With Nonlinear Models, Qin Cai
Detecting Chaotic Signals With Nonlinear Models, Qin Cai
Dissertations and Theses
In this thesis we apply chaotic dynamic data analysis to the area of discrete time signal processing. A newly developed Hidden Filter Hidden Markov Model is introduced in detection of chaotic signals. Numerical experiments have verified that this novel nonlinear model outperforms linear AR model in detecting chaotic signals buried by noise having similar power spectra. A simple Histogram Model is proposed which can also be used to do detection on the data sets with chaotic behavior. Receiver Operating Characteristics for a variety of noise levels and model classes are reported.
A New Approach To The Optimal Filtering Of Differential Phase Measurements Of Gps Signal In The Precision Survey, Shengan Wang
A New Approach To The Optimal Filtering Of Differential Phase Measurements Of Gps Signal In The Precision Survey, Shengan Wang
Dissertations and Theses
The Global Positioning System (GPS) has become popular research and application interests in surveying and many other areas. Nowadays, the accuracy of the Differential GPS can easily reach the order of a few meters. Yet, there are still many ways to exploit the GPS system signal carrier to improve the accuracy to less than meter level. In this thesis, a new approach to improve the accuracy to less than meter level is presented while the observer is in the dynamic situation. In order to reach the sub-meter accuracy, we measure on the carrier phase difference (The L1 carrier frequency is …