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.
In this work we present a comprehensive analysis of the scattered signals from buried landmine-like targets via accurate numerical modeling of Ground Penetrating Radar (GPR) responses considering various antenna-soil-target scenarios. Different characteristics in time and frequency domain are extracted and interpreted for each configuration. The acquired knowledge is useful to better understand the scattering mechanisms of subsurface objects and can be incorporated to target recognition procedures. A brief explanation of the results is also provided together with an overview of the most relevant temporal and spectral features encountered.
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