False Alarm Regulation for Off-Grid Target Detection With The Matched Filter
Pierre Develter, Jonathan Bosse, Olivier Rabaste, Philippe Forster, Jean Philippe Ovarlez
Abstract
In the state-of-the-art, the Probability of False Alarm (P<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FA</inf>)- threshold relationship for the popular Matched Filter (MF) is often derived assuming that unknown non-linear parameters lie on a grid. However, these parameters vary continuously in practice. This is known as the off-grid case. In this article, an asymptotic P<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FA</inf>-threshold relationship for the popular Matched Filter is derived in the off-grid case under complex white Gaussian noise hypothesis using expected Euler characteristics. This asymptotic relationship fits very well with corresponding Monte-Carlo trials in the moderate to low P<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FA</inf> regime.
BibTeX
@inproceedings{icassp2023_falsealarmregula,
title = {False Alarm Regulation for Off-Grid Target Detection With The Matched Filter},
author = {Pierre Develter and Jonathan Bosse and Olivier Rabaste and Philippe Forster and Jean Philippe Ovarlez},
booktitle = {ICASSP 2023},
year = {2023}
}