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Because most real-world signals, including speech, sonar, communication, and biological signals, are non-stationary, traditional signal analysis tools such as Fourier transforms are of limited use because they do not provide easily accessible information about the localization of a given frequency component. A more suitable approach for those studying non-stationary signals is the use of time frequency representations that are functions of both time and frequency.
Applications in Time-Frequency Signal Processing investigates the use of various time-frequency representations, such as the Wigner distribution and the spectrogram, in diverse application areas. Other books tend to focus on theoretical development. This book differs by highlighting particular applications of time-frequency representations and demonstrating how to use them. It also provides pseudo-code of the computational algorithms for these representations so that you can apply them to your own specific problems.
Written by leaders in the field, this book offers the opportunity to learn from experts. Time-Frequency Representation (TFR) algorithms are simplified, enabling you to understand the complex theories behind TFRs and easily implement them. The numerous examples and figures, review of concepts, and extensive references allow for easy learning and application of the various time-frequency representations.
Recent innovations in modern radar for designing transmitted
waveforms, coupled with new algorithms for adaptively selecting the
waveform parameters at each time step, have resulted in
improvements in tracking performance. Of particular interest are
waveforms that can be mathematically designed to have reduced
ambiguity function sidelobes, as their use can lead to an increase
in the target state estimation accuracy. Moreover, adaptively
positioning the sidelobes can reveal weak target returns by
reducing interference from stronger targets. The manuscript
provides an overview of recent advances in the design of
multicarrier phase-coded waveforms based on Bjorck
constant-amplitude zero-autocorrelation (CAZAC) sequences for use
in an adaptive waveform selection scheme for mutliple target
tracking. The adaptive waveform design is formulated using
sequential Monte Carlo techniques that need to be matched to the
high resolution measurements. The work will be of interest to both
practitioners and researchers in radar as well as to researchers in
other applications where high resolution measurements can have
significant benefits. Table of Contents: Introduction / Radar
Waveform Design / Target Tracking with a Particle Filter / Single
Target tracking with LFM and CAZAC Sequences / Multiple Target
Tracking / Conclusions
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