arXiv subjects

Marco Lanucara

Publications and source records attributed to Marco Lanucara.

3 recordsLinked to original sources

arXiv2026

Exact Autocorrelation of the Multiplicative Inverse of a Non-Zero-Mean Complex Gaussian Process

We study the spectral properties of a stochastic process obtained by multiplicative inversion of a non-zero-mean complex Gaussian process. We show that its autocorrelation function and power spectrum exist for most regular processes, and we derive a first order differential equation for the autocorrelation function, which follows from a demonstrated recurrence relation between the coefficients of its series expansion. Finally, we obtain a closed-form expression of the autocorrelation function based on the first and second order statistics of the underlying Gaussian process.

math.ST↗

arXiv2025

Noise performance of the complex monopulse ratio

The paper provides a characterization of the complex monopulse ratio in terms of autocorrelation and power spectral density of its fluctuations during satellite tracking, taking into account the presence of additive noise on sum and difference channels. The considered spectral structure and statistical distribution of the incoming signal is of interest for satellite missions. In particular it is assumed that the signal available at the monopulse processor after frequency down conversion contains a Gaussian term produced by low pass filtering of a constant envelope modulation, plus a monochromatic component representative of a possible residual carrier. The results can be used for optimizing the design of a monopulse tracking system.

eess.SP↗

arXiv2009

Resampling and requantization of band-limited Gaussian stochastic signals with flat power spectrum

A theoretical analysis, aimed at characterizing the degradation induced by the resampling and requantization processes applied to band-limited Gaussian signals with flat power spectrum, available through their digitized samples, is presented. The analysis provides an efficient algorithm for computing the complete {joint} bivariate discrete probability distribution associated to the true quantized version of the Gaussian signal and to the quantity estimated after resampling and requantization of the input digitized sequence. The use of Fourier transform techniques allows deriving {approximate} analytical expressions for the quantities of interest, as well as implementing their efficient computation. Numerical experiments are found to be in good agreement with the theoretical results, and confirm the validity of the whole approach.

cs.IT↗