학술논문

Spectral ship surveillance from space
Document Type
Conference
Source
2015 IEEE Applied Imagery Pattern Recognition Workshop (AIPR) Applied Imagery Pattern Recognition Workshop (AIPR), 2015 IEEE. :1-8 Oct, 2015
Subject
Bioengineering
Computing and Processing
General Topics for Engineers
Geoscience
Photonics and Electrooptics
Signal Processing and Analysis
Detectors
Covariance matrices
Oceans
Mathematical model
Clutter
Clouds
Detection algorithms
Language
ISSN
2332-5615
Abstract
Remote surveillance of the ocean will soon become a high priority for the U.S. Navy, as international threats to close strategic choke points intensify, as piracy flourishes, and as gaps in U.S. waters continue to permit illegal intrusions with contraband cargo. A critical need is arising to identify threats as early and as distant from our shores as possible. A growing constellation of spectrally-capable satellites can facilitate this function, which must be performed autonomously. Earth's total ocean area is 1014 (1 m)2 pixels. This paper develops a spectral anomaly detection algorithm that is based on a statistical mixture model of clouds and ocean. A real time implementable prototype version is derived using clairvoyant fusion methods. Development of a second generation version applicable to a more accurate clutter model is also described.