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.
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.
Stenger-Smith J.D.,Air Intelligence |
Lai W.W.,Air Intelligence |
Irvin D.J.,Materials and Systems Research |
Yandek G.R.,Air Force Research Lab |
Irvin J.A.,Texas State University
Journal of Power Sources | Year: 2012
A novel processing technique was used to solution cast films of poly(benzimidazo benzophenanthroline), (BBL), and the novel ladder polymer poly(4-aza-benzimidazo benzophenanthroline) (Py-BBL), which were used as cathode materials in Type IV electroactive polymer-based electrochemical capacitors (EPECs). This new processing technique involves co-casting the polymer from solution with a room temperature ionic liquid, 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide (EMIBTI). The new processing technique gave polymer films with superior transport properties and electrochemical stabilities, did not require a break-in period, and yielded higher charge capacity than the standard films. Co-cast films of BBL and Py-BBL were each incorporated into separate Type IV EPECs using poly(3,4-propylene dioxythiophene) (PProDOT) as the anode material. It was found that the PProDOT/BBL capacitors store, on average, about 50% more energy than a comparable PProDOT/Py-BBL EPEC. While PProDOT/BBL films have an energy density advantage at rates (power densities) less than 0.01 kW kg -1, PProDOT/Py-BBL EPECs are capable of delivering higher energy than the BBL EPECs at rates greater than 0.01 kW kg -1 (550 s per cycle). In fact, PProDOT/Py-BBL devices delivered more than ten times the energy density of PProDOT/BBL devices at 0.5 kW kg -1 (50 s per cycle). The PProDOT/Py-BBL EPECs were cycled for 10,000 cycles at 65% depth of discharge and maintained 96% of the initial energy and power density, whereas the PProDOT/BBL EPECs were cycled under the same conditions and lost more than 35% of the initial energy and power density after only 2300 cycles. © 2012 Elsevier B.V. All rights reserved.
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.
Li X.-B.,The Academy of Management |
Yang R.-J.,Air Intelligence |
Cheng W.,Air Intelligence
Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology | Year: 2013
Integration of radar and communication on the electronic war platform is an effective method to reduce their volume, electromagnetic interference. In allusion to mutual interference and incompatible issue between suitable wareforms design of integrated radar and communication, following the principle of signal sharing, integration of radar and communication system and the correspondence processing scheme is presented based on FM orthogonal multicarrier chirp signal. First, based on wideband ambiguity function, the characteristics of the multicarrier integrated signal are analyzed in detail. The system performance and signal processing of integrated signal are analyzed. Simulation results and theoretical analysis show that the integrated signal can satisfy conventional radar detection and have low bit error rate under 20% rate of spectrum overlapping.
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.
Feng S.,Air Intelligence
Optics Express | Year: 2010
We apply the equivalent theory to orthorhombic anisotropic materials and provide a general unit-cell design criterion for achieving a length-independent retrieval of the effective material parameters from a single layer of unit cells. We introduce a graphical retrieval method and phase unwrapping techniques. The graphical method utilizes the linear regression technique. Our method can reduce the uncertainty of experimental measurements and the ambiguity of phase unwrapping. Moreover, the graphical method can simultaneously determine the bulk values of the six effective material parameters, permittivity and permeability tensors, from a single layer of unit cells.
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.
Roberts M.J.,Air Intelligence |
Feng S.,Air Intelligence |
Moran M.B.,Air Intelligence |
Johnson L.F.,Air Intelligence
Journal of Nanophotonics | Year: 2010
Experiments were conducted to demonstrate a material with epsilon near zero (ENZ). Dimensions estimated by effective medium theory guided the fabrication of nanolaminate composites of silver and amorphous polycarbonate. This approach ensures that the ordinary component (not the extraordinary component) of the relative permittivity of a uniaxial material equals zero. The nanolaminates were characterized for optical properties using spectroscopic ellipsometry, reflectance, and transmittance. Simulations using both, a new scattering retrieval method, and an effective-medium approximation (EMA) were compared to the experimental results. These results indicate that nanolaminates should enable further exploration into the new optical phenomena predicted for ENZ materials. © 2010 Society of Photo-Optical Instrumentation Engineers.
Estabridis K.,Air Intelligence
2015 IEEE International Symposium on Technologies for Homeland Security, HST 2015 | Year: 2015
This paper proposes a ship recognition system that jointly classifies and learns from unlabeled data within a sparse representation framework. Compact dictionaries based on local descriptors serve as the basis for the classification system via l1 minimization techniques. Previous research has demonstrated the advantages of exploiting sparsity within the recognition context. Creating a dictionary based on invariant descriptors provides robustness to changes in illumination and to affine transformations. Traditional approaches assume that the training data will span future test samples implying that the training set includes a complete object representation. Such data sets are difficult to obtain and in the end the system's performance is highly dependent on the training data sets. This framework implements a flexible learning approach where dictionaries can be augmented or updated with relevant data from unlabeled test samples. © 2015 IEEE.