scholarly journals Direct Wideband Coherent Localization by Distributed Antenna Arrays

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4582 ◽  
Author(s):  
Nenad Vukmirović ◽  
Miljko Erić ◽  
Miloš Janjić ◽  
Petar M. Djurić
Keyword(s):  
Antenna Arrays ◽  
Position Estimation ◽  
Small Cells ◽  
Music Algorithm ◽  
Signal Model ◽  
Localization Accuracy ◽  
Mean Squared Errors ◽  
3D Space ◽  
Distributed Antenna ◽  
Cramer Rao Bound

We address wideband direct coherent localization of a radio transmitter by a distributed antenna array in a multipath scenario with spatially-coherent line-of-sight (LoS) signal components. Such a signal scenario is realistic in small cells, especially indoors in the mmWave range. The system model considers collocated time and phase synchronized receiving front-ends with antennas distributed in 3D space at known locations connected to the front-ends via calibrated coaxial cables or analog radio frequency over fiber links. The signal model assumes spherical wavefronts. We propose two ML-type algorithms (for known and unknown transmitter waveforms) and a subspace-based SCM-MUSIC algorithm for wideband direct coherent position estimation. We demonstrate the performance of the methods by Monte Carlo simulations. The results show that even in multipath environments, it is possible to achieve localization accuracy that is much better (by two to three orders of magnitude) than the carrier wavelength. They also suggest that the methods that do not exploit knowledge of the waveform have mean-squared errors approaching the Cramér–Rao bound.

scholarly journals A Sensor-Driven Analysis of Distributed Direction Finding Systems Based on UAV Swarms

Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2659 ◽  
Author(s):  
Zhong Chen ◽  
Shihyuan Yeh ◽  
Jean-Francois Chamberland ◽  
Gregory H. Huff
Keyword(s):  
Data Collection ◽  
Antenna Arrays ◽  
Collection System ◽  
Music Algorithm ◽  
System Framework ◽  
Data Collection System ◽  
Multiple Signal Classification ◽  
Source Case ◽  
Aerial Vehicle ◽  
Cramer Rao Bound

This paper reports on the research of factors that impact the accuracy and efficiency of an unmanned aerial vehicle (UAV) based radio frequency (RF) and microwave data collection system. The swarming UAVs (agents) can be utilized to create micro-UAV swarm-based (MUSB) aperiodic antenna arrays that reduce angle ambiguity and improve convergence in sub-space direction-of-arrival (DOA) techniques. A mathematical data model is addressed in this paper to demonstrate fundamental properties of MUSB antenna arrays and study the performance of the data collection system framework. The Cramer–Rao bound (CRB) associated with two-dimensional (2D) DOAs of sources in the presence of sensor gain and phase coefficient is derived. The single-source case is studied in detail. The vector-space of emitters is exploited and the iterative-MUSIC (multiple signal classification) algorithm is created to estimate 2D DOAs of emitters. Numerical examples and practical measurements are provided to demonstrate the feasibility of the proposed MUSB data collection system framework using iterative-MUSIC algorithm and benchmark theoretical expectations.

scholarly journals Performance Limits of Direct Wideband Coherent 3D Localization in Distributed Massive MIMO Systems

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3401
Author(s):  
Nenad Vukmirović ◽  
Miljko Erić ◽  
Petar M. Djurić
Keyword(s):  
Massive Mimo ◽  
Mimo Systems ◽  
Position Estimation ◽  
Cellular Systems ◽  
Small Cells ◽  
Performance Limits ◽  
Signal To Noise ◽  
Square Roots ◽  
3D Space ◽  
Noise Threshold

We address the accuracy of wideband direct position estimation of a radio transmitter via a distributed antenna array in 5G cellular systems. Our derivations are based only on the presence of spatially coherent line-of-sight (LoS) signal components, which is a realistic assumption in small cells, especially in the mmWave range. The system model considers collocated time and phase synchronized receiving front-ends with antennas distributed in 3D space at known locations and connected to the front-ends via calibrated coaxial cables or analog radio-frequency-over-fiber links. Furthermore, the signal model assumes spherical wavefronts. We derive the Cramér-Rao bounds (CRBs) for two implementations of the system: with (a) known signals and (b) random Gaussian signals. The results show how the bounds depend on the carrier frequency, number of samples used for estimation, and signal-to-noise ratios. They also show that increasing the number of antennas (such as in massive MIMO systems) considerably improves the accuracy and lowers the signal-to-noise threshold for localization even for non-cooperative transmitters. Finally, our derivations show that the square roots of the bounds are two to three orders of magnitude below the carrier wavelength for realistic system parameters.

scholarly journals Full snapshot reconstruction in hybrid architecture antenna arrays

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Maria Trigka ◽  
Christos Mavrokefalidis ◽  
Kostas Berberidis
Keyword(s):  
Antenna Array ◽  
Antenna Arrays ◽  
Communication Systems ◽  
Linear Array ◽  
Research Work ◽  
Hybrid Architecture ◽  
Angle Of Arrival ◽  
Music Algorithm ◽  
Array Structures ◽  
Signal Sources

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).

Design methods for ULA‐based directional antenna arrays by shaping the Cramér–Rao bound functions

2018 ◽  
Vol 12 (2) ◽  
pp. 247-254 ◽  
Author(s):  
Minqiu Chen ◽  
Xingpeng Mao ◽  
Ran Guo ◽  
Ming‐Yang Cao ◽  
Yongtan Liu
Keyword(s):  
Antenna Arrays ◽  
Directional Antenna ◽  
Design Methods ◽  
Cramer Rao Bound

Sequence Localization Algorithm Based on 3D Voronoi Diagram in Wireless Sensor Network

2014 ◽  
Vol 644-650 ◽  
pp. 4422-4426 ◽  
Author(s):  
Xi Yang ◽  
Jun Liu
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Voronoi Diagram ◽  
Wireless Sensor ◽  
Weighted Estimate ◽  
Localization Algorithm ◽  
Simulation Experiments ◽  
Localization Accuracy ◽  
3D Space ◽  
Unknown Node

For nodes’ self-localization in wireless sensor networks (WSN), a new localization algorithm called Sequence Localization algorithm based on 3D Voronoi diagram (SL3V) is proposed, which uses 3D Voronoi diagram to divide the localization space.It uses the polyhedron vertices as the virtual beacon nodes and constructs the rank sequence table of virtual beacon nodes. Then it computes Kendall coefficients of the ranks in the optimal rank sequence table and that of the unknown node. Finally, it realizes the weighted estimate of the unknown node by normalization processing Kendall coefficients. Simulation experiments prove that itcan obviously improve the localization accuracy compared with the traditional 2D sequence-based localization and can satisfy the need of localization for 3D space.

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