
Proceedings Paper
Recent ATR and fusion algorithm improvements for multiband sonar imageryFormat | Member Price | Non-Member Price |
---|---|---|
$14.40 | $18.00 |
![]() |
GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. | Check Access |
Paper Abstract
An improved automatic target recognition processing string has been developed. The overall processing string consists
of pre-processing, subimage adaptive clutter filtering, normalization, detection, data regularization, feature extraction,
optimal subset feature selection, feature orthogonalization and classification processing blocks. The objects that are
classified by the 3 distinct ATR strings are fused using the classification confidence values and their expansions as
features, and using "summing" or log-likelihood-ratio-test (LLRT) based fusion rules. The utility of the overall
processing strings and their fusion was demonstrated with new high-resolution three-frequency band sonar imagery. The
ATR processing strings were individually tuned to the corresponding three-frequency band data, making use of the new
processing improvement, data regularization; this improvement entails computing the input data mean, clipping the data
to a multiple of its mean and scaling it, prior to feature extraction and resulted in a 3:1 reduction in false alarms. Two
significant fusion algorithm improvements were made. First, a nonlinear exponential Box-Cox expansion (consisting of
raising data to a to-be-determined power) feature LLRT fusion algorithm was developed. Second, a repeated application
of a subset Box-Cox feature selection / feature orthogonalization / LLRT fusion block was utilized. It was shown that
cascaded Box-Cox feature LLRT fusion of the ATR processing strings outperforms baseline "summing" and single-stage
Box-Cox feature LLRT algorithms, yielding significant improvements over the best single ATR processing string results,
and providing the capability to correctly call the majority of targets while maintaining a very low false alarm rate.
Paper Details
Date Published: 5 May 2009
PDF: 11 pages
Proc. SPIE 7303, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIV, 73030C (5 May 2009); doi: 10.1117/12.818542
Published in SPIE Proceedings Vol. 7303:
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIV
Russell S. Harmon; J. Thomas Broach; John H. Holloway, Editor(s)
PDF: 11 pages
Proc. SPIE 7303, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIV, 73030C (5 May 2009); doi: 10.1117/12.818542
Show Author Affiliations
Tom Aridgides, Lockheed Martin Maritime Systems & Sensors (United States)
Manuel Fernández, Lockheed Martin Maritime Systems & Sensors (United States)
Published in SPIE Proceedings Vol. 7303:
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIV
Russell S. Harmon; J. Thomas Broach; John H. Holloway, Editor(s)
© SPIE. Terms of Use
