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Fayetteville, AR, United States

The Israeli Air Intelligence Group is a unit of the Israel Defense Forces Air Force. Like other IDF intelligence gathering bodies, it is professionally subordinate to the IDF's Intelligence Directorate. Lamdan is responsible for the formulation of the aerial intelligence picture, and participates in forging the overall intelligence view as part of the Israeli Intelligence Community. It operates several research and collection units, including the Technical Assistance Unit which analyzes aerial photography, and the Zoom Unit which studies the procurement of new aircraft. Lamdan also operates alongside Aman's Visual Intelligence Branch and the Naval Intelligence Department's Visual Intelligence Unit. Lamdan is currently headed by Brigadier-General Yaacov Shahrbani. Wikipedia.

Nguyen V.C.,Nanyang Technological University | Chen L.,Nanyang Technological University | Halterman K.,Air Intelligence
Physical Review Letters | Year: 2010

We theoretically investigate microwave transmission through a zero-index metamaterial loaded with dielectric defects. The metamaterial is impedance matched to free space, with the permittivity and permeability tending towards zero over a given frequency range. By simply varying the radii and permittivities of the defects, total transmission or reflection of the impinging electromagnetic wave can be achieved. The proposed defect structure can offer advances in shielding or cloaking technologies without restricting the object's viewpoint. Active control of the observed exotic transmission and reflection signatures can occur by incorporating tunable refractive index materials such as liquid crystals and BaSrTiO3. © 2010 The American Physical Society.

Zhu J.,University of California at Irvine | Krivorotov I.N.,University of California at Irvine | Halterman K.,Air Intelligence | Valls O.T.,University of Minnesota
Physical Review Letters | Year: 2010

The superconducting transition temperature Tc of a ferromagnet (F)-superconductor (S)-ferromagnet trilayer depends on the mutual orientation of the magnetic moments of the F layers. This effect has been previously observed in F/S/F systems as a Tc difference between parallel and antiparallel configurations of the F layers. Here we report measurements of Tc in CuNi/Nb/CuNi trilayers as a function of the angle between the magnetic moments of the CuNi ferromagnets. The observed angular dependence of Tc is in qualitative agreement with a F/S proximity theory that accounts for the odd triplet component of the condensate predicted to arise for noncollinear orientation of the magnetic moments of the F layers. © 2010 The American Physical Society.

Yarbrough A.W.,Air Intelligence | Mendenhall M.J.,Air Force Institute of Technology | Martin R.K.,Air Force Institute of Technology | Fiorino S.T.,Air Force Institute of Technology
IEEE Transactions on Geoscience and Remote Sensing | Year: 2014

Accurate target detection and classification in hyperspectral imagery require that the spectral measurements by the imager match as closely as possible the known 'true' target as collected under controlled conditions and stored in a target database. Therefore, the effect of the radiation source and the atmosphere must be factored out of the result before detection is attempted. Our objective is to evaluate detection error due to the error in estimating the atmospherics. We apply a range of atmospheric water vapor profiles, corresponding to different relative humidities, to a model-based prediction of the radiative transfer to examine the effect of water vapor on simulated hyperspectral imagery. These profiles are taken from known distribution percentiles as obtained from historic meteorological measurements close to the sites being simulated. We quantify the expected detection error for the adaptive matched filter, as measured by the receiver operating characteristic (ROC) and the area under the ROC curve, given the range of atmospheric conditions in the historic profile. We discover that, depending on the target, and given the uncertainty as to the true atmospheric conditions, detection rates improve on average across the historic range when we assume the atmospheric profile is at the 35th percentile of atmospheric relative humidity instead of the 50th percentile. © 2013 IEEE.

Estabridis K.,Air Intelligence
Conference Record - Asilomar Conference on Signals, Systems and Computers | Year: 2012

This paper proposes an adaptive recognition system that integrates local and global features while jointly classifying and learning from unlabeled data. Dictionaries based on local descriptors serve as the basis for the recognition system and at the same time provide spatial-mappings derived from the location of the selected features during classification, via l1 minimization techniques. The mappings provide a global object representation that is utilized to discriminate among classes with candidate descriptors. Additionally updating or learning new local descriptors (via non-parametric Bayes) from unlabeled data within a dictionary framework, provides the flexibility needed when training data is limited. © 2012 IEEE.

DiPietro R.S.,Lincoln Laboratory | Manolakis D.G.,Lincoln Laboratory | Lockwood R.B.,Lincoln Laboratory | Cooley T.,Air Force Research Lab | Jacobson J.,Air Intelligence
Optical Engineering | Year: 2012

One of the fundamental challenges for a hyperspectral imaging surveillance system is the detection of sub-pixel objects in background clutter. The background surrounding the object, which acts as interference, provides the major obstacle to successful detection. One algorithm that is widely used in hyperspectral detection and successfully suppresses the background in many situations is the matched filter detector. However, the matched filter also produces false alarms in many situations. We use three simple and well-established concepts - the target-background replacement model, the matched filter, and Mahalanobis distance - to develop the matched filter with false alarm mitigation (MF-FAM), a dual-threshold detector capable of eliminating many matched filter false alarms. We compare this algorithm to the mixture tuned matched filter (MTMF), a popular approach to matched filter false alarm mitigation found in the ENVI® software environment. The two algorithms are shown to produce nearly identical results using real hyperspectral data, but the MF-FAM is shown to be operationally, computationally, and theoretically simpler than the MTMF. © 2012 Society of Photo-Optical Instrumentation Engineers (SPIE).

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