scholarly journals Performance Analysis of Single-Step Localization Method Based on Matrix Eigen-Perturbation Theory with System Errors

Electronics ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 235
Author(s):  
Tianzhu Qin ◽  
Bin Ba ◽  
Daming Wang

Direct position determination (DPD) is a novel technique in passive localization field recently, receiving superior localization performance compared with the conventional two-step method. The DPD estimator using Doppler shifts is first proposed by Weiss, but it is not suitable for antenna arrays. Additionally, the performance analysis of this method with system errors is absent. This study discusses the single-step localization problem based on moving arrays and exhibits the performance analysis via matrix eigen-perturbation theory with system errors. First, the DPD method using angle of arrival and Doppler shifts is introduced. Then, by adding the eigenvalue perturbations to the estimated Hermitian matrix, the asymptotic linear formulation of localization errors is derived. Consequently, the mean square error of the DPD method is available. Finally, Cramér–Rao bound without system errors is presented, providing a benchmark for the best localization precision and revealing the influence of system errors on the localization precision. Simulation results demonstrate the theoretical analysis in this study.

1983 ◽  
Vol 49 (01) ◽  
pp. 024-027 ◽  
Author(s):  
David Vetterlein ◽  
Gary J Calton

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.


Author(s):  
Maria Trigka ◽  
Christos Mavrokefalidis ◽  
Kostas Berberidis

AbstractIn the context of this research work, we study the so-called problem of full snapshot reconstruction in hybrid antenna array structures that are utilized in mmWave communication systems. It enables the recovery of the snapshots that would have been obtained if a conventional (non-hybrid) uniform linear antenna array was employed. The problem is considered at the receiver side where the hybrid architecture exploits in a novel way the antenna elements of a uniform linear array. To this end, the recommended scheme is properly designed so as to be applicable to overlapping and non-overlapping architectures. Moreover, the full snapshot recoverability is addressed for two cases, namely for time-varying and constant signal sources. Simulation results are also presented to illustrate the consistency between the theoretically predicted behaviors and the simulated results, and the performance of the proposed scheme in terms angle-of-arrival estimation, when compared to the conventional MUSIC algorithm and a recently proposed hybrid version of MUSIC (H-MUSIC).


Author(s):  
Matilde Sanchez-Fernandez ◽  
Vahid Jamali ◽  
Jaime Llorca ◽  
Antonia Tulino

2019 ◽  
Vol 116 (40) ◽  
pp. 19848-19856 ◽  
Author(s):  
Alexandre Goy ◽  
Girish Rughoobur ◽  
Shuai Li ◽  
Kwabena Arthur ◽  
Akintunde I. Akinwande ◽  
...  

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.


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

1997 ◽  
Vol 786 (1) ◽  
pp. 99-106 ◽  
Author(s):  
Travis H. Tani ◽  
Jamie M. Moore ◽  
Thomas W. Patapoff

2009 ◽  
Vol 08 (03) ◽  
pp. 323-332 ◽  
Author(s):  
RA'A SAID ◽  
NIDAL ALSHWAWREH ◽  
YOUSEF HAIK

To add to the development efforts in enhancing the capabilities of localized electrodeposition (LED) fabrication technique, this paper presents serial and parallel deposition algorithms to fabricate array microstructures. Such arrays can be implemented as microsensors in neural recording applications or as antenna arrays in ultra high frequency applications. Also, magnetic tip microarrays for tissue engineering can be realized. In the case of serial fabrication, an array of high aspect ratio microstructures is realized using the conventional single-tip microelectrode while implementing a multistep fabrication algorithm. In this algorithm, the fabricated microstructure elements within the array are realized one at a time. In the parallel deposition algorithm, the array is realized using a multitip array microelectrode while implementing a single step fabrication algorithm. In this algorithm, the microstructure elements within the array are fabricated simultaneously. The proposed algorithms are compared through a demonstration of fabricated array microstructures.


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