scholarly journals Reflector-aided direct locations of multiple signals in the presence of small reflector position biases

2018 ◽  
Vol 14 (4) ◽  
pp. 155014771877130
Author(s):  
Jiexin Yin ◽  
Ding Wang ◽  
Ying Wu ◽  
Zhidong Wu
Keyword(s):  
Signal To Noise Ratio ◽  
Single Step ◽  
Multiple Sources ◽  
Step Method ◽  
Signal Model ◽  
Multiple Signals ◽  
First Order ◽  
Localization Performance ◽  
Cramer Rao Bound ◽  
Theoretical Results

Direct position determination (DPD) is a single-step method that localizes transmitters from sensor outputs without computing intermediate parameters. It outperforms conventional two-step localization methods, especially under low signal-to-noise ratio conditions. This article proposes a reflector-aided DPD algorithm for multiple signals of known waveforms received by an array observer. In previous studies, reflector-aided localization has always required very precise locations of reflectors. Therefore, the localization performance depends sensitively on accurately knowing each reflector position. This study considers the presence of small biases in reflector locations. To make the problem tractable, we simplify the signal model through an approximation using the first-order Taylor expansion and then directly localize multiple sources in a decoupled manner. Unlike most DPDs that presume noise is spatially uncorrelated, our study imposes no restriction on the correlation structure of noise, allowing this algorithm to be used in more general scenarios. In addition, we derive the Cramér–Rao bound expression and perform an analysis of the direct locations of multiple signals when the reflector positions are assumed accurate but in fact have small biases. Simulation results corroborate the theoretical results and a good localization performance of the proposed algorithm in the presence of small reflector position biases.

scholarly journals A Single-Step Method for Over-the-Horizon Geolocation Using Importance Sampling

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Jiexin Yin ◽  
Ding Wang ◽  
Bin Yang ◽  
Xin Yang
Keyword(s):  
Importance Sampling ◽  
Low Complexity ◽  
Single Step ◽  
Step Method ◽  
Position Information ◽  
Importance Function ◽  
Localization Performance ◽  
Monte Carlo Importance Sampling ◽  
Simulation Results ◽  
Cramer Rao Bound

This paper investigates the geolocation for an over-the-horizon (OTH) transmitter observed by widely separated arrays. We propose a maximum likelihood (ML) based direct position determination (DPD) method to directly locate the transmitter in a single step by exploiting the position information embedded in azimuth angles. The Monte Carlo importance sampling (IS) technique is employed to find an approximate global solution to this DPD problem, where the importance function analogous to Gaussian distribution is derived. This enables the transmitter to be precisely located with low complexity in a noniterative manner. Additionally, we derive the Cramér–Rao bound (CRB) expression for the investigated problem. The simulation results corroborate the superior localization performance of the proposed method with respect to the conventional two-step approaches and the iterative DPD method.

Purification of Urokinase from Complex Mixtures Using Immobilized Monoclonal Antibody Against Urokinase Light Chain

1983 ◽  
Vol 49 (01) ◽  
pp. 024-027 ◽  
Author(s):  
David Vetterlein ◽  
Gary J Calton
Keyword(s):  
Monoclonal Antibody ◽  
Light Chain ◽  
Culture Media ◽  
Biological Fluids ◽  
Single Step ◽  
High Yield ◽  
Step Method ◽  
Commercial Preparation ◽  
E Coli ◽  
Tissue Culture Media

SummaryThe preparation of a monoclonal antibody (MAB) against high molecular weight (HMW) urokinase light chain (20,000 Mr) is described. This MAB was immobilized and the resulting immunosorbent was used to isolate urokinase starting with an impure commercial preparation, fresh urine, spent tissue culture media, or E. coli broth without preliminary dialysis or concentration steps. Monospecific antibodies appear to provide a rapid single step method of purifying urokinase, in high yield, from a variety of biological fluids.

Analysis of a New Mixed Finite Volume Method

2003 ◽  
Vol 3 (1) ◽  
pp. 189-201 ◽  
Author(s):  
Ilya D. Mishev
Keyword(s):  
Finite Volume Method ◽  
Finite Volume ◽  
Elliptic Equations ◽  
Variable Pressure ◽  
Order Error ◽  
First Order ◽  
Scalar Variable ◽  
Volume Method ◽  
Well Posed ◽  
Theoretical Results

AbstractA new mixed finite volume method for elliptic equations with tensor coefficients on rectangular meshes (2 and 3-D) is presented. The implementation of the discretization as a finite volume method for the scalar variable (“pressure”) is derived. The scheme is well suited for heterogeneous and anisotropic media because of the generalized harmonic averaging. It is shown that the method is stable and well posed. First-order error estimates are derived. The theoretical results are confirmed by the presented numerical experiments.

scholarly journals High-resolution limited-angle phase tomography of dense layered objects using deep neural networks

2019 ◽  
Vol 116 (40) ◽  
pp. 19848-19856 ◽  
Author(s):  
Alexandre Goy ◽  
Girish Rughoobur ◽  
Shuai Li ◽  
Kwabena Arthur ◽  
Akintunde I. Akinwande ◽  
...  
Keyword(s):  
Integrated Circuit ◽  
Deep Neural Networks ◽  
Tomographic Reconstruction ◽  
Synthetic Data ◽  
Single Step ◽  
Training Set ◽  
Step Method ◽  
3 Dimensional ◽  
Dimensional Reconstruction ◽  
Optical Domain

We present a machine learning-based method for tomographic reconstruction of dense layered objects, with range of projection angles limited to ±10○. Whereas previous approaches to phase tomography generally require 2 steps, first to retrieve phase projections from intensity projections and then to perform tomographic reconstruction on the retrieved phase projections, in our work a physics-informed preprocessor followed by a deep neural network (DNN) conduct the 3-dimensional reconstruction directly from the intensity projections. We demonstrate this single-step method experimentally in the visible optical domain on a scaled-up integrated circuit phantom. We show that even under conditions of highly attenuated photon fluxes a DNN trained only on synthetic data can be used to successfully reconstruct physical samples disjoint from the synthetic training set. Thus, the need for producing a large number of physical examples for training is ameliorated. The method is generally applicable to tomography with electromagnetic or other types of radiation at all bands.

A Single-Step Method for the Isolation of Antithrombin IIP

Vox Sanguinis ◽  
1984 ◽  
Vol 47 (6) ◽  
pp. 397-405
Author(s):  
Milan Wickerhauser ◽  
Craigenne Williams
Keyword(s):  
Single Step ◽  
Step Method

Single step method for the accurate concentration determination of polysorbate 80

1997 ◽  
Vol 786 (1) ◽  
pp. 99-106 ◽  
Author(s):  
Travis H. Tani ◽  
Jamie M. Moore ◽  
Thomas W. Patapoff
Keyword(s):  
Single Step ◽  
Polysorbate 80 ◽  
Step Method ◽  
Concentration Determination

Models for New Corrugated and Porous Solar Air Collectors under Transient Operation

2017 ◽  
Vol 42 (1) ◽  
Author(s):  
Qahtan Adnan Abed ◽  
Viorel Badescu ◽  
Adrian Ciocanea ◽  
Iuliana Soriga ◽  
Dorin Bureţea
Keyword(s):  
Climatic Conditions ◽  
Meteorological Conditions ◽  
Bias Error ◽  
First Order ◽  
Solar Air Collector ◽  
Section Surface ◽  
South Eastern Europe ◽  
Main Components ◽  
Theoretical Results ◽  
Good Agreement

AbstractMathematical models have been developed to evaluate the dynamic behavior of two solar air collectors: the first one is equipped with a V-porous absorber and the second one with a U-corrugated absorber. The collectors have the same geometry, cross-section surface area and are built from the same materials, the only difference between them being the absorbers. V-corrugated absorbers have been treated in literature but the V-porous absorbers modeled here have not been very often considered. The models are based on first-order differential equations which describe the heat exchange between the main components of the two types of solar air heaters. Both collectors were exposed to the sun in the same meteorological conditions, at identical tilt angle and they operated at the same air mass flow rate. The tests were carried out in the climatic conditions of Bucharest (Romania, South Eastern Europe). There is good agreement between the theoretical results and experiments. The average bias error was about 7.75 % and 10.55 % for the solar air collector with “V”-porous absorber and with “U”-corrugated absorber, respectively. The collector based on V-porous absorber has higher efficiency than the collector with U-corrugated absorber around the noon of clear days. Around sunrise and sunset, the collector with U-corrugated absorber is more effective.

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