Title :
Synthetic SAR/IR database generation for sensor fusion-based A.T.R.
Author :
Jin-Ju Won;Sungho Kim;Youngrea Cho;Woo-Jin Song;So-Hyun Kim
Author_Institution :
Department of Electronic Engineering Yeungnam University, Gyeonsan, Korea
Abstract :
Recently, the sensor fusion research has been in progress for effective ground target detection. SAR and IR sensors are complementary because the IR sensor has a high resolution, SAR sensor is not effected by the weather. In research, The DB of the SAR/IR sensor is essential. But database(DB) of the SAR/IR sensor dose not exist or is not released. It is also difficult to acquire the DB directly because of cost and environmental issues. Therefore, this paper proposed a method to build the DB with synthetic image generation simulator OKTAL-SE. We generate day and night images, and compare the features.
Keywords :
"Atmospheric modeling","Robot sensing systems","Image generation","Meteorology","Computational modeling","Sensor fusion","Object detection"
Conference_Titel :
Ubiquitous Robots and Ambient Intelligence (URAI), 2015 12th International Conference on
DOI :
10.1109/URAI.2015.7358893