Fast Algorithm for Adaptive Chirplet Decomposition

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Resource Overview

A rapid algorithm for adaptive chirplet decomposition, addressing the challenges of numerous unknown parameters and implementation difficulties. This algorithm computes the quadratic phase function of signals to determine energy concentration along chirp rate curves, enabling simultaneous estimation of chirplet parameters (chirp rate, time center, and amplitude) via spectral peak detection. Initial frequency and bandwidth estimates are obtained through de-chirping techniques. The effectiveness of this method is validated through simulation results.

Detailed Documentation

To address parameter uncertainty and implementation challenges in adaptive chirplet decomposition of known signals, Reference [1] proposes a novel rapid chirplet decomposition algorithm. The algorithm computes the quadratic phase function to determine that signal energy concentrates along chirp rate curves. Through spectral peak detection implemented via fast Fourier transforms, simultaneous estimation of chirplet parameters (chirp rate, temporal center, and amplitude) is achieved. Furthermore, de-chirping techniques employing frequency demodulation allow estimation of initial frequency and bandwidth. Simulation results using MATLAB/Octave implementations validate the algorithm's effectiveness, providing a rapid and reliable solution for parameter estimation in adaptive chirplet decomposition.

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