Incoherent detection of man-made objects obscured by foliage in forest area

• Published in: 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
• Main Authors: Pettersson, Mats, Vu, Viet Thuy, Gomes, Natanael Rodrigues, Dammert, Patrik, Hellsten, Hans
• Format: Conference Object
• Language: English
• Published: Blekinge Tekniska Högskola, Institutionen för matematik och naturvetenskap 2017
• Subjects: Change Detection; LRT; Rayleigh; SAR; Other Electrical Engineering; Electronic Engineering; Information Engineering; Annan elektroteknik och elektronik; Northern Sweden
• Online Access: http://urn.kb.se/resolve?urn=urn:nbn:se:bth-15923; https://doi.org/10.1109/IGARSS.2017.8127347

The paper introduces a new likelihood ratio test (LRT) for incoherent detection of man-made objects obscured by foliage in forest area. The test is performed to detect changes between a reference image and a surveillance image. The method is developed for change detection in high resolution Synthetic Aperture Radar (SAR). For simplicity and lack of more appropriate models, the new LRT is still based on simple and efficient models. If there is no man-made object, the statistical model for clutter and noise of two images will be a bivariate Rayleigh distribution. In contrary, a joint distribution of Rayleigh and uniform is used to model for target, clutter, and noise. The proposed LRT is evaluated using radar data acquired by CARABAS in northern Sweden. The probability of detection is up to 96% with much less than one false alarm per square kilometer. © 2017 IEEE.