Time-frequency analysis of spread spectrum based communication and audio watermarking systems
- Time-frequency analysis of spread spectrum based communication and audio watermarking systems
In this study, we present novel applications of time-frequency analysis to spread spectrum based communication and audio watermarking systems. Our objective is to detect and estimate non-stationary signals, such as chirps, that are characterized by directional elements in the time-frequency plane. Towards this goal, we model non-stationary signals using the matching pursuit decomposition algorithm, generate a positive time-frequency representation of the signal model using the Wigner-Ville distribution and estimate the energy varying directional elements using a line detection algorithm based on the Hough-Radon transform.Spread spectrum communication systems frequently encounter nonstationary signalswith energy varying directional elements as hostile jamming signals. In this thesis, we develop a new interference excision algorithm for spread spectrum communication systems based on the directional element estimation algorithm. At the receiver, we first excise the interference from the spread spectrum signal before despreadingand data symbol detection. The new algorithm can excise single and multicomponent interferences such that the spread spectrum system can reliably detect the transmitted message symbols even, when the interference power exceeds the jammingmargin of the system. We verify the effectiveness of the interference excision algorithm using simulation studies.Watermarking is the process of embedding imperceptible data into the host signal for marking the copyright ownership. The embedded data should be extractable to prove ownership. Watermarking systems face problems similar to those in spreadspectrum communication systems, namely, intentional attacks by the adversaries. Inwatermarking, the adversaries try to obliterate the embedded watermark in order toprevent its detection by authorized parties. In this thesis, we develop a spread spectrum audio watermarking scheme, where we embed perceptually shaped linear chirps as watermark messages. The directional elements of the chirp signals represent different watermark messages. We extract the watermark by first detecting the transmittedmessage symbols in the spread spectrum signal. We then use the directional elementestimation algorithm based on the time-frequency analysis as a post-processing tool to minimize the effects of hostile attacks on the extractability of the embedded watermark. We demonstrate the robustness of the algorithm by extracting the watermarkcorrectly after common signal processing operations representing hostile attacks byadversaries.