1 February 1998 Constant false alarm rate detection of point targets using distributed sensors
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The problem of orthogonalization of multiple satellite images, focusing at the same field of view, is studied in this paper for constant false alarm rate (CFAR) point target detection. Information fusion techniques are incorporated. The Karhunen-Loéve (K-L) orthogonalization method offers the best CFAR detection performance. However, it requires central fusion. It is shown that a version of the Gram-Schmidt (G-S) orthogonalization method, which preprocesses data in a pipeline form, offers a comparable CFAR detection to that of the K-L method. Point target CFAR detection is carried out by employing various fusion approaches on the orthogonal data. Sensor level fusion with quality information is shown to be preferable when the proposed sequential G-S orthogonalization is applied. The proposed CFAr approach is applied to dissimilar sensors and avoids overloading the communication channel transmitting only in the case of target detection. Trade-off studies and experimental results on real and simulated data are presented.
George A. Lampropoulos, Vassilis Anastassopoulos, and James F. Boulter "Constant false alarm rate detection of point targets using distributed sensors," Optical Engineering 37(2), (1 February 1998). https://doi.org/10.1117/1.601626
Published: 1 February 1998
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Cited by 15 scholarly publications.
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KEYWORDS
Sensors

Signal to noise ratio

Target detection

Image fusion

Data fusion

Sensor fusion

Lawrencium

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