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On the efficient computation of range and Doppler data in noise radar

Published online by Cambridge University Press:  04 February 2019

Christoph Wasserzier  and
Gaspare Galati
Christoph Wasserzier*
Affiliation:
Tor Vergata University, via del Politecnico 1, Rome, Italy Fraunhofer Institute for High Frequency Physics and Radar Techniques FHR, Fraunhoferstr. 20, 53343 Wachtberg, Germany
Gaspare Galati
Affiliation:
Tor Vergata University, via del Politecnico 1, Rome, Italy CNIT, National Inter-University Consortium for Telecommunications
*
Author for correspondence: Christoph Wasserzier [email protected]
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Abstract

In noise radar, digital signal processing algorithms for implementing the computation of the Cross Ambiguity Function through range correlation and Doppler compensation call for optimized solutions. In fact, to achieve a high coherent processing gain, they often compute a large amount of data beyond the maximum range and/or the maximum radial velocity of interest, adding useless information. A novel, efficient algorithm, called Range Filter Bank, is proposed to implement a scope-tailored computation of range/Doppler data in continuous emission noise radar. Downstream its theoretical analysis, the algorithm has been applied to a real-life case study based on dedicated field experiments, in which good quality kinematic data of a car moving at various speeds have been extracted.

Keywords

Noise radar technologyrange filter bankrange-doppler mapmoving target detection
Type
MIKON 2018
Information
International Journal of Microwave and Wireless Technologies , Volume 11 , Special Issue 7: MIKON 2018 / EuMW 2018 (Part II) , September 2019 , pp. 584 - 592
Copyright
Copyright © Cambridge University Press and the European Microwave Association 2019 

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