Traffic monitoring with spaceborne SAR-Theory, simulations, and experiments

Authors:
Stefan Hinz;Franz Meyer;Michael Eineder;Richard Bamler
Affiliations:
Remote Sensing Technology, Technische Universitaet Muenchen, Germany1urlwww.RemoteSensing-TUM.de/lmf1;Remote Sensing Technology Institute, German Aerospace Center, Germany2urlwww.imf.dlr.de2;Remote Sensing Technology Institute, German Aerospace Center, Germany2urlwww.imf.dlr.de2;Remote Sensing Technology, Technische Universitaet Muenchen, Germany1urlwww.RemoteSensing-TUM.de/lmf1 and Remote Sensing Technology Institute, German Aerospace Center, Germany2urlwww.imf.dlr.de2
Venue:
Computer Vision and Image Understanding
Year:
2007

Citing 0
Cited 3

Moving target indication via RADARSAT-2 multichannel synthetic aperture radar processing

EURASIP Journal on Advances in Signal Processing - Special issue on advances in multidimensional synthetic aperture radar signal processing
Crossing road monitoring system based on adaptive decision for illegal situation

Applied Soft Computing
Directional moving target indication: a novel SAR ambiguity function for traffic monitoring

Journal of Electrical and Computer Engineering

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper reviews the theoretical background for upcoming dual-channel radar satellite missions to monitor traffic from space and exemplifies the potentials and limitations by real data. In general, objects that move during the illumination time of the radar will be imaged differently than stationary objects. If the assumptions incorporated in the focusing process of the synthetic aperture radar (SAR) principle are not met, a moving object will appear both displaced and blurred. To study the impact of these (and related) distortions in focused SAR images, the analytic relations between an arbitrarily moving point scatterer and its conjugate in the SAR image have been reviewed and adapted to dual-channel satellite specifications. Furthermore, a specific detection scheme is proposed that integrates complementary detection and velocity estimation algorithms with knowledge derived from external sources as, e.g., road databases. Results using real SAR data are presented to validate the theory.