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Institution

Defence Research Agency

About: Defence Research Agency is a based out in . It is known for research contribution in the topics: Synthetic aperture radar & Radar. The organization has 1211 authors who have published 1109 publications receiving 31542 citations.


Papers
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Journal ArticleDOI
TL;DR: In this article, the authors extended the dual boundary element method to allow new cracks to initiate in response to the sudden increase in the loading coming from stress concentrations when existing cracks intersect with boundaries or with each other.

2 citations

Proceedings ArticleDOI
08 Apr 2019
TL;DR: An iterative procedure is presented for calculating system capabilities for more than two systems or sub-capabilities and error propagation from estimated capability changes to system capability values is investigated in order to provide methods to evaluate errors of derived quantities.
Abstract: Mathematical methods for modeling military capabilities are presented with numerical values for three capability areas and two systems. Probabilistic modeling methods are extended with the use of analytical S-shaped growth curves for capability areas and system capabilities. We illustrate how the derived results, i.e. system capabilities and derivatives of system capabilities, can be used to discover different characteristics and trends from the data for capability areas. Our earlier results for two systems are generalized. An iterative procedure is presented for calculating system capabilities for more than two systems or sub-capabilities. Error propagation from estimated capability changes to system capability values is investigated in order to provide methods to evaluate errors of derived quantities.

2 citations

Patent
04 Jul 1996
TL;DR: In this paper, the shape of the sensor signal is compared with that of the corresponding reference signal over a finite time window, using e.g. correlation techniques, and a fault is declared when the shapes differ by a prescribed amount.
Abstract: The sensor fault detector is one in which each sensor signal is compared with a reference signal provided by e.g. a model of the system being monitored. Prior art sensor fault detectors subtract the output of the sensor and the corresponding reference signal from each other, and a fault is declared when the residual difference exceeds a prescribed threshold. However, modelling errors (such as scaling discrepancies), d.c bias and noise mean that faults are often wrongly declared, or alternatively that only large faults can be detected. These problems are overcome according to the invention by comparing the "shape" of the sensor signal with that of the corresponding reference signal (i.e. comparing the signal outlines) over a finite time window, using e.g. correlation techniques. A fault is declared when the shapes differ by a prescribed amount.

2 citations

Journal ArticleDOI
TL;DR: An efficient machine-oriented representation for security labels is described, along with the means of converting between this and a wide variety of human readable, textual formats.

2 citations

13 May 1992
TL;DR: In this paper, the European committee, Eurocae WG33, proposed system test levels for the susceptibility testing of display systems, based on a statistical study of available aircraft EM transfer function measurements.
Abstract: Within the United States and Europe, committees have been formed to draft requirements and test procedures for the certification of civil aircraft, against the effects of the external RF environment created by ground, ship and airborne transmitters. The European committee, Eurocae WG33, proposed system test levels for the susceptibility testing of display systems, based on a statistical study of available aircraft EM transfer function measurements. The paper describes the procedures used to derive from this study, generic transfer function curves, which have been included in the draft committee documentation for use in bulk current injection conducted susceptibility testing. >

2 citations


Authors

Showing all 1211 results

NameH-indexPapersCitations
Stephen M. Smith128501140104
Jonathan Knight8862537720
M. S. Skolnick7372822112
Alan Tennant7043316870
Richard J. Needs6935219528
Dan S. Henningson6636919038
John Rarity6543415562
Michael J. Uren442948408
Leigh T. Canham4216018268
A. G. Cullis4016111320
Richard A. Pethrick384106918
David S. Lee381138580
Neil Gordon3718137011
Pierfrancesco Lombardo363015018
Peter John Roberts31866679
Network Information
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20221
20219
202018
201910
20189
201713