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Dive into the research topics where Brian E. Fischer is active.

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Featured researches published by Brian E. Fischer.


IEEE Antennas and Propagation Magazine | 2014

Three-dimensional position and orientation measurements using magneto-quasistatic fields and complex image theory [measurements corner]

Brian E. Fischer; Ivan J. LaHaie; Darmindra D. Arumugam; Joshua D. Griffin; Daniel D. Stancil; David S. Ricketts

Traditional wireless position-location systems, operating using propagating waves, suffer reduced performance in non-line-of-sight (NLoS) applications. Traditional systems that use quasistatic fields have instead been limited to short ranges, progressive direction-finding applications, require RF fingerprinting, or do not provide complete immunity to dielectric obstacles (use of electric fields). These limitations impose severe restrictions in applications such as tracking an American football during game play, where position and orientation tracking may be required over long ranges, and when the line-of-sight (LoS) is blocked by groups of people. A technique using magneto-quasistatic fields and complex image theory was recently shown to circumvent these problems, and to enable accurate long-range one-dimensional and two-dimensional measurements. In this work, we present three-dimensional position and orientation measurements using the magneto-quasistatic system and complex image theory over an area of 27.43 m × 27.43 m. Inverting the theoretical expression for the voltage measured at the terminals of the receiving loops to determine three-dimensional position and orientation resulted in mean and median geometric position errors of 0.77 m and 0.71 m, respectively; inclination orientation mean and median errors of 9.67° and 8.24°, respectively; and azimuthal orientation mean and median errors of 2.84° and 2.25°, respectively.


IEEE Antennas and Propagation Magazine | 2013

Measurements corner: Causes of discrepancies between measurements and EM simulations of millimeter-wave antennas

Brian E. Fischer; Ivan J. LaHaie; M. D. Huang; Matti H. A. J. Herben; A. C. F. Reniers; P. F. M. Smulders

This article describes the possible factors that can introduce discrepancies between measurements and three-dimensional EM simulations of millimeter-wave (mm-wave) antennas. The effects of the choice of the simulation solver, the relative permittivity and the homogeneity of the substrate material, the manufacturing tolerance, and the measurement errors are discussed. It is concluded that a fair comparison between measurements and simulations of mm-wave antennas can only be made if all these possible causes of discrepancies are taken into account.This article describes the possible factors that can introduce discrepancies between measurements and three-dimensional EM simulations of millimeter-wave (mm-wave) antennas. The effects of the choice of the simulation solver, the relative permittivity and the homogeneity of the substrate material, the manufacturing tolerance, and the measurement errors are discussed. It is concluded that a fair comparison between measurements and simulations of mm-wave antennas can only be made if all these possible causes of discrepancies are taken into account.


ieee radar conference | 2014

T13 — Transformations for Radar Cross-Section (RCS) and imaging from monostatic near-field measurements

Ivan J. LaHaie; Brian E. Fischer

Summary form only given, as follows. True far-field (FF) radar cross-section (RCS) measurements of full-scale targets are often impractical to perform because of the large distances and/or large compact range reflector required to produce a plane wave illumination of the target. This fact has led to a requirement for techniques that can infer FF RCS from limited (specifically, monostatic-only) measurements in the near-field (NF) of the target. In this tutorial, we will present an in-depth derivation of a family of mature, self-consistent, and accurate near field RCS transformations that are based on models that are used in synthetic aperture, tomographic, and other forms of radar imaging. These image-based techniques have been successfully applied in practice to a wide range of targets and measurement configurations. The complete presentation was not made available for publication as part of the conference proceedings.


IEEE Antennas and Propagation Magazine | 2010

In memoriam: Ray King

Brian E. Fischer; Ivan J. LaHaie

Ray King, a retired Lawrence Livermore National Laboratory (LLNL) engineer, died February 21, 2010. He was 77. Born in Montrose, Colorado, on January 1, 1933, King grew up on a large ranch in the mountains outside of Montrose. He took great pride and enjoyment in his high school years as a member of FFA (Future Farmers of America), and became state President his senior year in high school.


IEEE Antennas and Propagation Magazine | 2008

Recent Microwave Absorber Wall-Reflectivity Measurement Methods [Measurements Corner]

Brian E. Fischer; Ivan J. LaHaie

The classical and widely used termination - VSWR method, used to measure the reflectivity of an absorber wall in an anechoic chamber, has been recently upgraded. This measurement (slotted-line measurement type) was in the past realized frequency by frequency, with an amplitude transmitter/receiver and one antenna on a moving cart. It is now possible to cover a complete frequency bandwidth without any movement with the advanced VSWR method (AVSWR), and also with the RCS method. These two complementary methods do not require antenna movement, and allow measuring complete bandwidths at the same time, where only a few frequencies were measured before. It is not an exaggeration to say that the progress is as high as the transition between the slotted-line measurement technique and automated vector network analyzers at the end of the 1970s.


international conference on electromagnetics in advanced applications | 2017

Model-Based optimization using ℓ 1 minimization for reducing the uncertainty in radar cross-section (RCS) measurements and predictions

Ivan J. LaHaie; Michael Blischke; Steven Cossmann; Brian E. Fischer; Mark Hawks

Our team at Integrity Applications Inc. (IAI) has worked extensively on radar cross-section (RCS) measurements and predictions and problems related to removal of background contamination, defect detection and localization, image editing and reconstruction (IER), sub-Nyquist interpolation, and near field-to-far field transformation (among others). In all cases, we have found that model-based optimization techniques using an ℓ1 minimization solver provide significantly improved performance with forward models as simple as isotropic point scatterers and as complex as rigorous method of moments (MoM) codes. In this overview paper, we present two simulated examples of model-based optimization using ℓ1 minimization from each end of that spectrum. The first involves the use of a sparsely-sampled set of RCS measurements to reduce the uncertainty in a MoM model due to unknown defects on the target. The model is then used to interpolate the sparsely-sampled RCS pattern data. The second involves the use of a dictionary of point scatterers and other linear basis functions to reduce the uncertainty in a set of RCS measurements due to additive contamination from clutter and noise.


IEEE Antennas and Propagation Magazine | 2010

Solicitation for Measurements Corner [Measurements Corner]

Brian E. Fischer

We welcome contributions for future installments of the Measurements Comer. Please send them to Brian Fischer and Ivan LaHaie, and they will be considered for publication as quickly as possible. Contributions can range from short notes to fun-length papers on all topics related to RF measurement technology and its applications, including antennas, propagation, materials, scattering, and radar cross section. New or unique measurement techniques are of particular interest.


IEEE Antennas and Propagation Magazine | 2010

Introduction [Measurements Corner]

Brian E. Fischer; Ivan J. LaHaie

The problem of detecting, locating, and tracking dismounts (moving people), using a distributed collection of simple and cheap narrowband (and, hence, low-resolution) radar devices, is an extremely challenging problem. It has been a topic of considerable research for the past several years. In particular, system performance is dependent upon both the positioning of the devices and the detection/tracking algorithms applied to the raw radar data. This months Measurements Comer paper describes a novel Bayes-optimal nonlinear filtering technique for the latter. It demonstrates that reasonable dismount tracking can be accomplished with 5–10m bistatic range-resolution systems.


IEEE Antennas and Propagation Magazine | 2010

Practical Illumination Uncertainty Assessment i-n Ground-Based Radar Measurements

Brian E. Fischer; Gary D. Dester; Timothy Conn; Richard W Hanberg

The models governing ground-bounce illumination have been well understood for decades. Previously referenced work examined the application of these models to three-dimensional geometries, and showed that illumination variation is a spatially dependent function of frequency. Illumination variation requires knowledge of the targets geometry and scattering characteristics in order to evaluate uncertainty. This paper leverages that work and further develops a short-time Fourier transform (STFT) method to extract frequency-domain scattering characteristics directly from target data. By utilizing at least two antenna heights in two separate measurements, ground-bounce geometries allow for useful target-feature characterization. This enables an assessment of spatial target uncertainty in the image domain, as well as for RCS; it further shows promise for illumination-error mitigation. This paper demonstrates this potential in simulation to support measurements collected at the National RCS Test Facility (NRTF), Holleman AFB, NM.


IEEE Antennas and Propagation Magazine | 2009

Dielectric Field Probes for Very-Near-Field and Compact-Near-Field Antenna Characterization

Brian E. Fischer; Ivan J. LaHaie; A. Capozzo; C. Curcio; G. D'e; A. Liseno; P. Vinetfi; M. Ameya; M. Hirose; S. Kurokawa; K. Komiyama

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Ivan J. LaHaie

General Dynamics Advanced Information Systems

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Daniel D. Stancil

North Carolina State University

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David S. Ricketts

North Carolina State University

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Gary D. Dester

Michigan State University

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Joshua D. Griffin

California Institute of Technology

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Leo C. Kempel

Michigan State University

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