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Aerospace 2017, 4(1), 11; doi:10.3390/aerospace4010011

Sense and Avoid Airborne Radar Implementations on a Low-Cost Weather Radar Platform

Intelligent Aerospace Radar Team (IART), School of Electrical and Computer Engineering, Advanced Radar Research Center (ARRC), University of Oklahoma, Norman, OK 73019-0390, USA
Garmin Aviation Weather Radar, Garmin International Inc., Olathe, KS 66062-3426, USA
Author to whom correspondence should be addressed.
Academic Editor: Konstantinos Kontis
Received: 12 January 2017 / Accepted: 21 February 2017 / Published: 1 March 2017
(This article belongs to the Special Issue Radar and Aerospace)
View Full-Text   |   Download PDF [8741 KB, uploaded 2 March 2017]   |  


Traditionally, multi-mission applications in airborne radar are implemented through very expensive phased array architectures. The emerging applications from civilian surveillance, on the other hand, prefer low-cost and low-SWaP (space, weight and power) systems. This study introduces asoftware-basedsolutionthatintendstouselow-costhardwareandadvancedalgorithms/processing backend to meet the remote sensing goals for multi-mission applications. The low-cost airborne radar platform from Garmin International is used as a representative example of the system platform. The focus of this study is the optimal operating mode, data quality and algorithm development in cases of all-weather sense and avoid (SAA) applications. The main challenges for the solution are the resolution limitation due to the small aperture size, limitations from the field-of-view (FOV) and the scan speed from mechanical scanning. We show that the basic operational needs can be satisfied with software processing through various algorithms. The concept and progress of polarimetric airborne radar for dual-function operations at X-band Generation 1 (PARADOX1) based on the platform are also discussed. View Full-Text
Keywords: multi-mission; airborne radar; iterative adaptive approach; adaptive pulse compression; matched filter multi-mission; airborne radar; iterative adaptive approach; adaptive pulse compression; matched filter

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Nepal, R.; Zhang, Y.; Blake, W. Sense and Avoid Airborne Radar Implementations on a Low-Cost Weather Radar Platform. Aerospace 2017, 4, 11.

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