Mean‐scatterer spacing estimates with spectral correlation

TLDR: This paper addresses the problem of estimating mean-scatterer spacing from the backscattered ultrasound signal using spectral redundancy characterized by the spectral autocorrelation (SAC) function, and results indicate that SAC- based estimates converge more reliably over smaller amounts of data than cepstrum-based estimates.

Abstract: An ultrasonic backscattered signal from material comprised of quasiperiodic scatterers exhibit redundancy over both its phase and magnitude spectra. This paper addresses the problem of estimating mean‐scatterer spacing from the backscattered ultrasound signal using spectral redundancy characterized by the spectral autocorrelation (SAC) function. Mean‐scatterer spacing estimates are compared for techniques that use the cepstrum and the SAC function. A‐scan models consist of a collection of regular scatterers with Gamma distributed spacings embedded in diffuse scatterers with uniform distributed spacings. The model accounts for attenuation by convolving the frequency dependent scattering centers with a time‐varying system response. Simulation results indicate that SAC‐based estimates converge more reliably over smaller amounts of data than cepstrum‐based estimates. A major reason for the performance advantage is the use of phase information by the SAC function, while the cepstrum uses a phaseless power spec...