An improved radar clutter suppression by simple neural network

Author:

Perďoch Jozef1ORCID,Gažovová Stanislava1,Pacek Miroslav1

Affiliation:

1. Department of Electronics Armed Forces Academy of General Milan Rastislav Stefanik Liptovsky Mikulas Slovakia

Abstract

AbstractThe presented paper is further focused on the presentation and subsequent assessment of utilising a proposed Neural Network (NN) with simple architecture in the role of a signal preprocessing algorithm for the Constant False Alarm Rate detector and the fixed threshold detector applied on a Range‐Doppler (RD) map with the aim of radar clutter impact reduction and minimisation of processing time. Based on a comparison of all tested algorithm results, it is possible to state that utilising the proposed NN with simple architecture led to reducing the impact of radar clutter when detecting radar targets on RD maps created from provided datasets. Comparing the mean processing time tmean values of all tested algorithms, the authors can state that employing the proposed NN in combination with the fixed threshold detector led to a significant improvement in the computation time needed for processing one RD map while preserving the suppression of radar clutter and detection of the radar targets.

Funder

Ministerstvo obrany Slovenskej republiky

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Advances in AI‐assisted radar sensing applications;IET Radar, Sonar & Navigation;2024-02

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