Browsing by Author "Gusland, Daniel"

Now showing items 1-3 of 3

    • Deep temporal detection - A machine learning approach to multiple-dwell target detection 

      Gusland, Daniel; Rolfsjord, Sigmund Johannes Ljosvoll; Torvik, Børge (2020)
      Detecting small targets, such as an Unmanned Aerial Vehicle (UAV) in high clutter and non-homogeneous environments is challenging for a radar system. Traditional Constant False Alarm Rate (CFAR) detectors have suboptimal ...

    • Imaging radar for navigation and surveillance on an autonomous unmanned ground vehicle capable of detecting obstacles obscured by vegetation 

      Gusland, Daniel; Torvik, Børge; Finden, Erlend; Gulbrandsen, Fredrik; Smestad, Ragnar (2019-09-16)
      The Norwegian Defence Research Establishment (FFI), has developed a multi purpose radar demonstrator for Intelligence, Surveillance and Reconnaissance (ISR) on the Off-road Light Autonomous Vehicle (OLAV) platform. The ...

    • LandX20 Experiment Report – experiment for future land warfare capabilities with focus on increased situational awareness and unmanned systems 

      Mathiassen, Kim; Baksaas, Magnus; Dyrdal Idar; Eikanger, Brage Gerdsønn; Gulbrandsen, Fredrik; Gusland, Daniel; Larsen, Martin Vonheim; Mentzoni, Eilert; Minos-Stensrud, Mathias; Moen, Jonas; Nilssen, Eivind Bergh; Nummedal, Olav Rune; Nygaard, Tønnes; Rolfsjord, Sigmund; Simonsen, Aleksander; Thoresen, Marius; Bakstad, Lorns Harald; Bentsen, Dan Helge; Eggesbø, Christian; Grimstvedt, Eirik Skjelbreid; Haavardsholm, Trym Vegard; Halsør, Marius; Hoelsæter, Øistein; Kolden, David; Krogstad, Thomas Røbekk; Macdonald, Robert Helseth; Nielsen, Niels Hygum; Nonsvik, Guri; Ruud, Else-Line Malene; Seehuus, Rikke Amilde; Wiig, Martin Syre; Østevold, Einar (2022-03-21)
      LandX20 was a collaborative experiment and demonstration where four research projects from the Norwegian Defence Research Establishment (FFI) participated. The goal of the experiment was two-fold. The first goal was to ...