Publisher DOI: 10.1371/journal.pone.0239911
Title: Analytical volume model for optimized spatial radar bat detection in onshore wind parks
Language: English
Authors: Kreutzfeldt, Jannes 
Floeter, Carolin 
Lingner, Thies 
Schmitz-Beuting, Lukas 
Reich, Michael 
Kunz, Veit Dominik 
Issue Date: 30-Sep-2020
Journal or Series Name: PLOS ONE 
Volume: 15
Issue: 9
Abstract: 
To develop mitigation measures for the protection of bats in close proximity to onshore wind turbines, new detection techniques covering large-scale environments and techniques, which are able to track individuals are required. Radar based observations, successfully applied in ornithological studies, offer a promising potential, but come with challenges regarding the comparability of measurements and noise interference (ground clutter) from objects within detection range. This paper presents improvements of a commercially available inexpensive pulse radar for 3D spatial detection of bat-sized objects in onshore wind parks. A new analytical spatial detection volume model is presented incorporating calibrated radar data and landscape parameters such as clutter. Computer simulation programs to process the analytical spatial detection volume model were developed. For model calibration, the minimum signal power of the radar was experimentally determined with the radar cross section (RCS) of an artificial bat (similar to Nyctalus noctula), resulting in a maximum detection range of 800 m and a corresponding RCS of 12.7 cm². Additionally, the spatial volume for radar detection was optimized with a clutter shielding fence (CSF). Adjusting the volume model by incorporating a theoretical model of the CSF, an extension of the detection volume by a factor of 2.5 was achieved, while the total volume of a 105° horizontal angular radar image section yields 0.0105 km³. Extrapolation and comparison with state-of-the-art acoustic bat detection result in a 270 times larger volume, confirming the large-scale detection capabilities of the pulse radar.
URI: http://hdl.handle.net/20.500.12738/10512
ISSN: 1932-6203
Review status: This version was peer reviewed (peer review)
Institute: Department Verfahrenstechnik 
Department Umwelttechnik 
Fakultät Life Sciences 
Competence Center Erneuerbare Energien und Energieeffizienz 
Type: Article
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