A Statistical Framework and Analysis for Perfect Radar Pulse Compression

Fuente: arXiv
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Main Authors: Chada, Neil K., Piiroinen, Petteri, Roininen, Lassi
Format: Preprint
Published: 2023
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author Chada, Neil K.
Piiroinen, Petteri
Roininen, Lassi
author_facet Chada, Neil K.
Piiroinen, Petteri
Roininen, Lassi
contents Perfect radar pulse compression coding is a potential emerging field which aims at providing rigorous analysis and fundamental limit radar experiments. It is based on finding non-trivial pulse codes, which we can make statistically equivalent, to the radar experiments carried out with elementary pulses of some shape. A common engineering-based radar experiment design, regarding pulse-compression, often omits the rigorous theory and mathematical limitations. In this work our aim is to develop a mathematical theory which coincides with understanding the radar experiment in terms of the theory of comparison of statistical experiments. We review and generalize some properties of the Itô measure. We estimate the unknown i.e. the structure function in the context of Bayesian statistical inverse problems. We study the posterior for generalized $d$-dimensional inverse problems, where we consider both real-valued and complex-valued inputs for posteriori analysis. Finally this is then extended to the infinite dimensional setting, where our analysis suggests the underlying posterior is non-Gaussian.
format Preprint
id arxiv_https___arxiv_org_abs_2308_07597
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle A Statistical Framework and Analysis for Perfect Radar Pulse Compression
Chada, Neil K.
Piiroinen, Petteri
Roininen, Lassi
Statistics Theory
Probability
Applications
Perfect radar pulse compression coding is a potential emerging field which aims at providing rigorous analysis and fundamental limit radar experiments. It is based on finding non-trivial pulse codes, which we can make statistically equivalent, to the radar experiments carried out with elementary pulses of some shape. A common engineering-based radar experiment design, regarding pulse-compression, often omits the rigorous theory and mathematical limitations. In this work our aim is to develop a mathematical theory which coincides with understanding the radar experiment in terms of the theory of comparison of statistical experiments. We review and generalize some properties of the Itô measure. We estimate the unknown i.e. the structure function in the context of Bayesian statistical inverse problems. We study the posterior for generalized $d$-dimensional inverse problems, where we consider both real-valued and complex-valued inputs for posteriori analysis. Finally this is then extended to the infinite dimensional setting, where our analysis suggests the underlying posterior is non-Gaussian.
title A Statistical Framework and Analysis for Perfect Radar Pulse Compression
topic Statistics Theory
Probability
Applications
url https://arxiv.org/abs/2308.07597