LADAR And FLIR Based Sensor Fusion For Automatic Target Classification

Fred Selzer; Dan Gutfinger

doi:10.1117/12.948935

5 January 1989 LADAR And FLIR Based Sensor Fusion For Automatic Target Classification

Fred Selzer, Dan Gutfinger

Proceedings Volume 1003, Sensor Fusion: Spatial Reasoning and Scene Interpretation; (1989) https://doi.org/10.1117/12.948935
Event: 1988 Cambridge Symposium on Advances in Intelligent Robotics Systems, 1988, Boston, MA, United States

Abstract

The purpose of this report is to show results of automatic target classification and sensor fusion for forward looking infrared (FLIR) and Laser Radar sensors. The sensor fusion data base was acquired from the Naval Weapon Center and it consists of coregistered Laser RaDAR (range and reflectance image), FLIR (raw and preprocessed image) and TV. Using this data base we have developed techniques to extract relevant object edges from the FLIR and LADAR which are correlated to wireframe models. The resulting correlation coefficients from both the LADAR and FLIR are fused using either the Bayesian or the Dempster-Shafer combination method so as to provide a higher confidence target classifica-tion level output. Finally, to minimize the correlation process the wireframe models are modified to reflect target range (size of target) and target orientation which is extracted from the LADAR reflectance image.

Citation Download Citation

Fred Selzer and Dan Gutfinger "LADAR And FLIR Based Sensor Fusion For Automatic Target Classification", Proc. SPIE 1003, Sensor Fusion: Spatial Reasoning and Scene Interpretation, (5 January 1989); https://doi.org/10.1117/12.948935

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