A Statistical Framework and Analysis for Perfect Radar Pulse Compression
Abstract
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 It\^{o} measure. We estimate the unknown i.e. the structure function in the context of Bayesian statistical inverse problems. We study the posterior for generalized -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.
Cite
@article{arxiv.2308.07597,
title = {A Statistical Framework and Analysis for Perfect Radar Pulse Compression},
author = {Neil K. Chada and Petteri Piiroinen and Lassi Roininen},
journal= {arXiv preprint arXiv:2308.07597},
year = {2025}
}