Articles | Volume 15
https://doi.org/10.5194/ars-15-77-2017
https://doi.org/10.5194/ars-15-77-2017
21 Sep 2017
 | 21 Sep 2017

Novel post-Doppler STAP with a priori knowledge information for traffic monitoring applications: basic idea and first results

André B. C. da Silva and Stefan V. Baumgartner

Abstract. This paper presents a novel a priori knowledge-based algorithm for traffic monitoring applications. The powerful post-Doppler space-time adaptive processing (PD STAP) is combined with a known road network obtained from the freely available OpenStreetMap (OSM) database. The road information is applied after the PD STAP for recognizing and rejecting false detections, and moreover, for repositioning the vehicles detected in the vicinity of the roads. The algorithm presents great potential for real-time processing, decreased hardware complexity and low costs compared to state-of-the-art systems. The processor was tested using real multi-channel data acquired by DLR's airborne system F-SAR. The experimental results are shown and discussed, and the novelties are highlighted (e.g., the benefits of using a priori knowledge information).

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Short summary
This paper presents a novel algorithm for traffic monitoring applications, where the powerful post-Doppler space-time adaptive processing (PD STAP) is combined with the OpenStreetMap database. The road map is applied after the PD STAP for recognizing and rejecting false detections, and for repositioning off-road vehicles. The algorithm was tested using real multi-channel data acquired by DLR’s airborne F-SAR. The experimental results are shown and discussed, and the novelties are highlighted.