Title :
A new approach to spectral estimation from irregular sampling
Author :
Bonacci, David ; Lacaze, Bernard
Author_Institution :
Signal Process. Unit, TESA Lab., Toulouse, France
Abstract :
This article addresses the problem of signal reconstruction, spectral estimation and linear filtering directly from irregularly-spaced samples of a continuous signal (or autocorrelation function in the case of random signals) when signal spectrum is assumed to be bounded. The number 2L of samples is assumed to be large enough so that the variation of the spectrum on intervals of width π/L is small. Reconstruction formulas are based on PNS (Periodic Nonuniform Sampling) schemes. They allow for reconstruction schemes not requiring regular resampling and suppress two stages in classical computations. The presented method can also be easily generalized to spectra in symmetric frequency bands (bandpass signals).
Keywords :
correlation methods; estimation theory; filtering theory; signal reconstruction; signal sampling; PNS schemes; autocorrelation function; bandpass signals; irregular sampling; linear filtering; periodic nonuniform sampling schemes; signal reconstruction problem; signal spectrum; spectral estimation; symmetric frequency bands; Accuracy; Estimation; Fourier transforms; Interpolation; Mirrors; Nonuniform sampling; Signal processing; Analytic signal; Nonuniform filtering; Periodic Nonuniform Sampling; Sampling theory; Signal reconstruction;
Conference_Titel :
Signal Processing Conference (EUSIPCO), 2014 Proceedings of the 22nd European
Conference_Location :
Lisbon