A successive parameter estimation algorithm for chirplet signal decomposition

• Published in: IEEE transactions on ultrasonics, ferroelectrics, and frequency control Vol. 53; no. 11; pp. 2121 - 2131
• Main Authors: Yufeng Lu, Demirli, R., Cardoso, G., Saniie, J.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.11.2006; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Acoustic signal processing; Acoustics; Algorithms; Chirp; Computer Simulation; Decomposition; Echoes; Exact sciences and technology; Frequency estimation; Fundamental areas of phenomenology (including applications); Image Enhancement - methods; Image Interpretation, Computer-Assisted - methods; Information Storage and Retrieval - methods; Mathematical models; Microstructure; Models, Biological; Models, Statistical; Numerical Analysis, Computer-Assisted; Parameter estimation; Performance analysis; Physics; Representations; Reproducibility of Results; Sensitivity and Specificity; Shape; Signal Processing, Computer-Assisted; Signal resolution; Signal to noise ratio; Studies; Time frequency analysis; Transforms; Ultrasonic imaging; Ultrasonic testing; Ultrasonography - methods; Parameter estimation; Source separation; Time frequency domain method; Image processing; Ultrasound imaging; Chirp pulse; Noise reduction; Signal estimation; Frequency estimation; Modeling; System identification; Acoustic image; Ultrasound; Target detection; Cramer Rao inequality; Non stationary condition; Pattern recognition; Multiple scattering; Physical properties; Arrival time; Image analysis; Minimal variance; Image sensor; Microstructure; Signal to noise ratio
• ISSN: 0885-3010; 1525-8955
• DOI: 10.1109/TUFFC.2006.152

In ultrasonic imaging systems, the patterns of detected echoes correspond to the shape, size, and orientation of the reflectors and the physical properties of the propagation path. However, these echoes often are overlapped due to closely spaced reflectors and/or microstructure scattering. The decomposition of these echoes is a major and challenging problem. Therefore, signal modeling and parameter estimation of the nonstationary ultrasonic echoes is critical for image analysis, target detection, arid object recognition. In this paper, a successive parameter estimation algorithm based on the chirplet transform is presented. The chirplet transform is used not only as a means for time-frequency representation, but also to estimate the echo parameters, including the amplitude, time-of-arrival, center frequency, bandwidth, phase, and chirp rate. Furthermore, noise performance analysis using the Cramer Rao lower bounds demonstrates that the parameter estimator based on the chirplet transform is a minimum variance and unbiased estimator for signal-to-noise ratio (SNR) as low as 2.5 dB. To demonstrate the superior time-frequency and parameter estimation performance of the chirplet decomposition, ultrasonic flaw echoes embedded in grain scattering, and multiple interfering chirplets emitted by a large, brown bat have been analyzed. It has been shown that the chirplet signal decomposition algorithm performs robustly, yields accurate echo estimation, and results in SNR enhancements. Numerical and analytical results show that the algorithm is efficient and successful in high-fidelity signal representation