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Moving target tracking in SAR data using combined exo- and endo-clutter processing


Henke, Daniel; Mendez Dominguez, Elias; Small, David; Schaepman, Michael E; Meier, Erich (2018). Moving target tracking in SAR data using combined exo- and endo-clutter processing. IEEE Transactions on Geoscience and Remote Sensing, 56(1):251-263.

Abstract

Detecting and tracking moving targets in synthetic aperture radar (SAR) data is a challenging task, demanding state-of-the-art processing methods and advanced SAR systems. Current approaches concentrate on the problem of either endo-clutter moving target tracking or exo-clutter moving target tracking, neglecting the advantages of a joint tracking framework. We present an approach relying on a combined exo- and endo-clutter processing scheme using SAR data with a high pulse repetition frequency. The main processing chain is subdivided into four major steps: 1) focusing of temporal and spatial overlapping SAR images; 2) extracting image statistics for each of these subaperture images in the endo- and exo-clutter domains; 3) subsequent tracking of both endo- and exo-clutter observations using multitarget unscented Kalman filtering; and 4) calculating real-world speeds and positions from the SAR image space coordinates using a road network. The results of this approach are validated and compared with ground-based measurements, and it is found that 100% of the vehicles were detected correctly with an accuracy in speed of 0.02±0.31 m/s and an average tracking time of ~28 s.

Abstract

Detecting and tracking moving targets in synthetic aperture radar (SAR) data is a challenging task, demanding state-of-the-art processing methods and advanced SAR systems. Current approaches concentrate on the problem of either endo-clutter moving target tracking or exo-clutter moving target tracking, neglecting the advantages of a joint tracking framework. We present an approach relying on a combined exo- and endo-clutter processing scheme using SAR data with a high pulse repetition frequency. The main processing chain is subdivided into four major steps: 1) focusing of temporal and spatial overlapping SAR images; 2) extracting image statistics for each of these subaperture images in the endo- and exo-clutter domains; 3) subsequent tracking of both endo- and exo-clutter observations using multitarget unscented Kalman filtering; and 4) calculating real-world speeds and positions from the SAR image space coordinates using a road network. The results of this approach are validated and compared with ground-based measurements, and it is found that 100% of the vehicles were detected correctly with an accuracy in speed of 0.02±0.31 m/s and an average tracking time of ~28 s.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Language:English
Date:2018
Deposited On:05 Dec 2017 16:30
Last Modified:27 Apr 2018 07:47
Publisher:Institute of Electrical and Electronics Engineers
ISSN:0196-2892
OA Status:Closed
Publisher DOI:https://doi.org/10.1109/TGRS.2017.2746262

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