  Target classification in bistatic low frequency radarPisane, Jonathan  ; ; et alScientific conference (2012, September 24) Detailed reference viewed: 15 (2 ULg)Passive radar testbed and preliminary experiments in recognition of non-cooperative aircraft intruding into controlled airspacePisane, Jonathan ; ; et alConference (2012, September 14) We consider the automatic classification of aircraft observed with a passive radar, thus using illuminators of opportunity. We deployed a testbed and developed classification algorithms. Preliminary tests ... [more ▼] We consider the automatic classification of aircraft observed with a passive radar, thus using illuminators of opportunity. We deployed a testbed and developed classification algorithms. Preliminary tests show a correct recognition rate of 72%. [less ▲] Detailed reference viewed: 12 (2 ULg)Automatic real-time collection of RCS of airplanes in a real bistatic low-frequency configuration using a software defined passive radar based on illuminators of opportunityPisane, Jonathan ; ; et alin Proceedings of the 2012 IEEE Radar Conference (2012, May) Detailed reference viewed: 17 (6 ULg)Target classification system based on the characterization of targets by subspacesPisane, Jonathan ; ; Verly, Jacques in Proceedings of 2011 IEEE CIE International Conference on Radar (2011, October) Detailed reference viewed: 16 (3 ULg)Passive target classification based on low-frequency bistatic backscattering coefficientsPisane, Jonathan ; ; Verly, Jacques Conference (2010, June) In this paper, we describe a new automatic target recognition method for classifying targets according to their bistatic backscattering coefficients. The classification model is based on the construction of ... [more ▼] In this paper, we describe a new automatic target recognition method for classifying targets according to their bistatic backscattering coefficients. The classification model is based on the construction of subspaces, one per target class. Results show an overall correct classification rate of about 83%, indicating that our method seems to be valid. Further improvements of the algorithm are also discussed. [less ▲] Detailed reference viewed: 28 (7 ULg)Target classification of experimentally-acquired low-frequency backscattering coefficients by construction of subspacesPisane, Jonathan ; ; Verly, Jacques Poster (2010, April) Detailed reference viewed: 23 (3 ULg)Range-dependence compensation in airborne bistatic STAP radar for partially-calibrated conformal antenna arrays; ; et al Conference (2008) Detailed reference viewed: 4 (0 ULg)High-resolution clutter-power estimation for range-dependence compensation in conformal-array STAP; ; et al Conference (2008) Detailed reference viewed: 7 (0 ULg)Knowledge-aided Array Calibration for Registration-based Range-dependence Compensation in Airborne STAP Radar with Conformal Antenna Arrays; ; et al Conference (2007) Detailed reference viewed: 1 (0 ULg)New methodology for generating realistic data for evaluation of performance of radar STAP algorithms; ; Verly, Jacques et alConference (2007) Detailed reference viewed: 3 (0 ULg) |
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