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An adaptive sensing approach for the detection of small UAV: First investigation of static sensor network and moving sensor platform

: Laurenzis, M.; Hengy, S.; Hammer, Marcus; Hommes, A.; Johannes, W.; Giovanneschi, F.; Rassy, O.; Bacher, E.; Schertzer, S.; Poyet, J.-M.


Kadar, I. ; Society of Photo-Optical Instrumentation Engineers -SPIE-, Bellingham/Wash.:
Signal Processing, Sensor/Information Fusion, and Target Recognition XXVII : 15-19 April 2018, Orlando, Florida
Bellingham, WA: SPIE, 2018 (Proceedings of SPIE 10646)
Paper 106460S, 10 S.
Conference "Signal Processing, Sensor/Information Fusion, and Target Recognition" <27, 2018, Orlando/Fla.>
Fraunhofer IOSB ()
Fraunhofer FHR ()
unmanned aerial vehicle; detection; tracking; data fusion

Fusion of information in heterogeneous multi-modal sensor networks has been proven to enhance sensing capabilities of ground troops to detect and track small unmanned aerial vehicles flying at low altitude. Nevertheless, the area coverage of a static sensor network could be permanently or temporally impacted by geographic topologies or moving obstacles which could reduce the local sensing probabilities. An additional moving sensor platform can be used to temporarily enhance sensing capabilities. First theoretical analysis and experimental field trials are presented using a static sensor network consisting of acoustical antenna array, a stationary FMCW RADAR and a passive/active optical sensor unit. Additionally, a measurement vehicle was applied, equipped with passive/active optical sensing devices. While the sensor network was used to monitor a stationary area with a sensor dependent sensing coverage, the measurement vehicle was used to obtain additional information outside the sensing range of the network or behind obstacles. A fusion of these data sets can provide an increased situational awareness. Limitations and improvements of this approach are discussed.