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GMTI in circular Sar data using STAP


Casalini, Emiliano; Henke, Daniel; Meier, Erich (2016). GMTI in circular Sar data using STAP. In: 2016 Sensor Signal Processing for Defence (SSPD), Edinburgh, United Kingdom, 22 September 2016 - 23 September 2016. IEEE, online.

Abstract

This paper presents method and results of a Ground Moving Target Indication (GMTI) experiment using multichannel Synthetic Aperture Radar (M-SAR) data collected by the four channel F-SAR system. The proposed approach is based on sub-aperture processing, Space-Time Adaptive Processing (STAP), constant false alarm rate (CFAR) thresholding and geocoding. The results are validated and compared with results of the same data set from a previous approach based on a combination of single-channel (SC) and Along-Track Interferometry (ATI) detections. It is shown that the STAP-based technique guarantees better performances when detecting moving targets with a small Radar Cross Section (RCS).

Abstract

This paper presents method and results of a Ground Moving Target Indication (GMTI) experiment using multichannel Synthetic Aperture Radar (M-SAR) data collected by the four channel F-SAR system. The proposed approach is based on sub-aperture processing, Space-Time Adaptive Processing (STAP), constant false alarm rate (CFAR) thresholding and geocoding. The results are validated and compared with results of the same data set from a previous approach based on a combination of single-channel (SC) and Along-Track Interferometry (ATI) detections. It is shown that the STAP-based technique guarantees better performances when detecting moving targets with a small Radar Cross Section (RCS).

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Additional indexing

Item Type:Conference or Workshop Item (Paper), not_refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Scopus Subject Areas:Physical Sciences > Computer Networks and Communications
Physical Sciences > Signal Processing
Physical Sciences > Electrical and Electronic Engineering
Physical Sciences > Acoustics and Ultrasonics
Physical Sciences > Instrumentation
Physical Sciences > Artificial Intelligence
Language:English
Event End Date:23 September 2016
Deposited On:07 Jan 2022 08:09
Last Modified:24 Apr 2022 07:04
Publisher:IEEE
OA Status:Closed
Publisher DOI:https://doi.org/10.1109/sspd.2016.7590602