scholarly journals Single-pixel polarimetric direction of arrival estimation using programmable coding metasurface aperture

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
The Viet Hoang ◽  
Vincent Fusco ◽  
Muhammad Ali Babar Abbasi ◽  
Okan Yurduseven
Keyword(s):  
Single Channel ◽  
Polarization State ◽  
Plane Waves ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Dynamically Reconfigurable ◽  
Waveform Diversity ◽  
Retrieval Technique ◽  
Incident Waves ◽  
Single Pixel

AbstractThis paper presents a single-pixel polarimetric compressive sensing (CS)-based direction of arrival (DoA) estimation technique using a cavity backed programmable coding metasurface aperture. The single-pixel DoA retrieval technique relies on a dynamically modulated waveform diversity, enabling spatially incoherent radiation masks to encode the incoming plane waves on the radar aperture using a single channel. The polarimetric nature of the wave-chaotic coded metasurface ensures that the DOA estimation is sensitive to the polarization state of the incoming waves. We show that the polarimetric single-pixel DoA concept can be realized by encoding the polarization information of the incoming waves at the physical layer level within the antenna. A dynamically reconfigurable wave-chaotic metasurface, which possesses a structured sparsity of dual-polarized coded metamaterial elements, is proposed for the proof of concept. It is shown that by encoding and compressing the source generated far-field incident waves into a single channel, we can retrieve high fidelity polarimetric DoA information from compressed measurements.

scholarly journals Single-Pixel Polarimetric Direction of Arrival Estimation Using Programmable Coding Metasurface Aperture

2021 ◽  
Author(s):  
The Viet Hoang ◽  
Vincent Fusco ◽  
Muhammad Ali Babar Abbasi ◽  
Okan Yurduseven
Keyword(s):  
Single Channel ◽  
Polarization State ◽  
Plane Waves ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Dynamically Reconfigurable ◽  
Retrieval Technique ◽  
Spatio Temporal ◽  
Incident Waves ◽  
Single Pixel

Abstract This paper presents a single-pixel polarimetric compressive sensing (CS)-based direction of arrival (DoA) estimation technique using a cavity backed programmable coding metasurface aperture. The single-pixel DoA retrieval technique relies on a dynamically modulated waveform diversity, enabling spatially incoherent radiation masks to encode the incoming plane waves on the radar aperture using a single channel. The polarimetric nature of the wave-chaotic coding metasurface ensures that DOA estimation considers the sensitivity of the structure to the polarization state of the incoming waves. We show that the polarimetric single-pixel DoA concept can be enabled by encoding the polarization information of the incoming waves at the physical layer level within the antenna. A dynamically reconfigurable wave-chaotic metasurface, that possesses a structured sparsity of dual-polarized coded metamaterial elements, is proposed for the proof of concept. It is also shown that by encoding and compressing the source generated far-field incident waves into a single channel using spatio-temporal incoherent measurement modes generated by the coded programmable metasurface, we can retrieve high fidelity polarimetric DoA information from compressed measurements.

scholarly journals Frequency-Diverse Computational Direction of Arrival Estimation Technique

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Okan Yurduseven ◽  
Muhammad Ali Babar Abbasi ◽  
Thomas Fromenteze ◽  
Vincent Fusco
Keyword(s):  
Plane Wave ◽  
Spatial Information ◽  
Single Channel ◽  
Plane Waves ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Estimation Technique ◽  
Frequency Diversity ◽  
Millimetre Wave ◽  
Single Antenna

Abstract We present a frequency-diverse based direction of arrival (DoA) estimation technique for millimetre-wave (mmW) 5G channel sounding. Frequency-diversity enables the creation of spatially incoherent radiation masks to encode the plane-wave signals incident on the radar aperture using a single antenna. Leveraging the frequency-diversity concept, spatial information of the plane-wave projections on the radar aperture is retrieved, resulting in high-fidelity DoA estimations by means of a simple Fourier transform operation applied to the retrieved plane-wave projection patterns. It is demonstrated that using the frequency-diversity concept, DoA estimation can be achieved through a simple frequency sweep, compressing the incoming plane-waves into a single channel through the transfer function of the radar aperture. This results in a significant simplification in the system hardware, requiring only a single antenna to achieve DoA estimation. It is also shown that the proposed technique can simultaneously detect the DoA information for multiple sources with a diffraction limited resolution.

Multiple Signal Direction of Arrival (DoA) Estimation for a Switched-beam System Using Neural Networks

PIERS Online ◽  
2007 ◽  
Vol 3 (8) ◽  
pp. 1160-1164 ◽  
Author(s):  
Konstantinos A. Gotsis ◽  
E. G. Vaitsopoulos ◽  
Katherine Siakavara ◽  
J. N. Sahalos
Keyword(s):  
Neural Networks ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Multiple Signal ◽  
Beam System

Direction of Arrival Estimation Under Near-Field Interference Using Matrix Filter

2015 ◽  
Vol 23 (04) ◽  
pp. 1540007 ◽  
Author(s):  
Guolong Liang ◽  
Wenbin Zhao ◽  
Zhan Fan
Keyword(s):  
Near Field ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Direction Of Arrival Estimation ◽  
Far Field ◽  
Data Simulation ◽  
Estimation Algorithms ◽  
Simulation Results

Direction of arrival (DOA) estimation is of great interest due to its wide applications in sonar, radar and many other areas. However, the near-field interference is always presented in the received data, which may result in degradation of DOA estimation. An approach which can suppress the near-field interference and preserve the far-field signal desired by using a spatial matrix filter is proposed in this paper and some typical DOA estimation algorithms are adjusted to match the filtered data. Simulation results show that the approach can improve capability of DOA estimation under near-field inference efficiently.

scholarly journals Analysis of Dual-Band Direction of Arrival Estimation in Multipath Scenarios

Electronics ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1236
Author(s):  
Alessandro Cidronali ◽  
Edoardo Ciervo ◽  
Giovanni Collodi ◽  
Stefano Maddio ◽  
Marco Passafiume ◽  
...  
Keyword(s):  
Multiple Access ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Dual Band ◽  
Second Step ◽  
Frequency Division ◽  
Simulation Environment ◽  
Full Wave ◽  
Wide Range ◽  
Localization Systems

The present paper analyzes the performance of localization systems, based on dual-band Direction of Arrival (DoA) approach, in multi-path affected scenarios. The implemented DoA estimation, which belongs to the so-called Space and Frequency Division Multiple Access (SFDMA) technique, takes advantage of the use of two uncorrelated communication carrier frequencies, as already demonstrated by the authors. Starting from these results, this paper provides, first, the methodology followed to describe the localization system in the proposed simulation environment, and, as a second step, describes how multi-path effects may be taken into account through a set of full-wave simulations. The latter follows an approach based on the two-ray model. The validation of the proposed approach is demonstrated by simulations over a wide range of virtual scenarios. The analysis of the results highlights the ability of the proposed approach to describe multi-path effects and confirms enhancements in DoA estimation as experimentally evaluated by the same authors. To further assess the performance of the aforementioned simulation environment, a comparison between simulated and measured results was carried out, confirming the capability to predict DoA performance.

scholarly journals An Enhanced Smoothed L0-Norm Direction of Arrival Estimation Method Using Covariance Matrix

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4403
Author(s):  
Ji Woong Paik ◽  
Joon-Ho Lee ◽  
Wooyoung Hong
Keyword(s):  
Covariance Matrix ◽  
Phased Array ◽  
Null Space ◽  
Estimation Method ◽  
Direction Of Arrival ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Direction Of Arrival Estimation ◽  
Improve Performance ◽  
Space Projection

An enhanced smoothed l0-norm algorithm for the passive phased array system, which uses the covariance matrix of the received signal, is proposed in this paper. The SL0 (smoothed l0-norm) algorithm is a fast compressive-sensing-based DOA (direction-of-arrival) estimation algorithm that uses a single snapshot from the received signal. In the conventional SL0 algorithm, there are limitations in the resolution and the DOA estimation performance, since a single sample is used. If multiple snapshots are used, the conventional SL0 algorithm can improve performance in terms of the DOA estimation. In this paper, a covariance-fitting-based SL0 algorithm is proposed to further reduce the number of optimization variables when using multiple snapshots of the received signal. A cost function and a new null-space projection term of the sparse recovery for the proposed scheme are presented. In order to verify the performance of the proposed algorithm, we present the simulation results and the experimental results based on the measured data.

scholarly journals Spectral Domain Sparse Representation for DOA Estimation of Signals with Large Dynamic Range

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5164
Author(s):  
Jacob Compaleo ◽  
Inder J. Gupta
Keyword(s):  
Sparse Representation ◽  
Antenna Array ◽  
Dynamic Range ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Single Step ◽  
Window Function ◽  
Spectral Domain ◽  
Low Sidelobe ◽  
Weighting Window

Recently, we proposed a Spectral Domain Sparse Representation (SDSR) approach for the direction-of-arrival estimation of signals incident to an antenna array. In the approach, sparse representation is applied to the conventional Bartlett spectra obtained from snapshots of the signals received by the antenna array to increase the direction-of-arrival (DOA) estimation resolution and accuracy. The conventional Bartlett spectra has limited dynamic range, meaning that one may not be able to identify the presence of weak signals in the presence of strong signals. This is because, in the conventional Bartlett spectra, uniform weighting (window) is applied to signals received by various antenna elements. Apodization can be used in the generation of Bartlett spectra to increase the dynamic range of the spectra. In Apodization, more than one window function is used to generate different portions of the spectra. In this paper, we extend the SDSR approach to include Bartlett spectra obtained with Apodization and to evaluate the performance of the extended SDSR approach. We compare its performance with a two-step SDSR approach and with an approach where Bartlett spectra is obtained using a low sidelobe window function. We show that an Apodization Bartlett-based SDSR approach leads to better performance with just single-step processing.

scholarly journals A Direction-of-Arrival Estimation Algorithm Based on Compressed Sensing and Density-Based Spatial Clustering and Its Application in Signal Processing of MEMS Vector Hydrophone

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2191
Author(s):  
Huichao Yan ◽  
Ting Chen ◽  
Peng Wang ◽  
Linmei Zhang ◽  
Rong Cheng ◽  
...  
Keyword(s):  
Compressed Sensing ◽  
Spatial Clustering ◽  
Direction Of Arrival ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Cluster Center ◽  
Direction Of Arrival Estimation ◽  
Vector Hydrophone ◽  
Regularization Parameters ◽  
Selection Of

Direction of arrival (DOA) estimation has always been a hot topic for researchers. The complex and changeable environment makes it very challenging to estimate the DOA in a small snapshot and strong noise environment. The direction-of-arrival estimation method based on compressed sensing (CS) is a new method proposed in recent years. It has received widespread attention because it can realize the direction-of-arrival estimation under small snapshots. However, this method will cause serious distortion in a strong noise environment. To solve this problem, this paper proposes a DOA estimation algorithm based on the principle of CS and density-based spatial clustering (DBSCAN). First of all, in order to make the estimation accuracy higher, this paper selects a signal reconstruction strategy based on the basis pursuit de-noising (BPDN). In response to the challenge of the selection of regularization parameters in this strategy, the power spectrum entropy is proposed to characterize the noise intensity of the signal, so as to provide reasonable suggestions for the selection of regularization parameters; Then, this paper finds out that the DOA estimation based on the principle of CS will get a denser estimation near the real angle under the condition of small snapshots through analysis, so it is proposed to use a DBSCAN method to process the above data to obtain the final DOA estimate; Finally, calculate the cluster center value of each cluster, the number of clusters is the number of signal sources, and the cluster center value is the final DOA estimate. The proposed method is applied to the simulation experiment and the micro electro mechanical system (MEMS) vector hydrophone lake test experiment, and they are proved that the proposed method can obtain good results of DOA estimation under the conditions of small snapshots and low signal-to-noise ratio (SNR).

scholarly journals Uncertainties in cloud phase and optical thickness retrievals from the Earth Polychromatic Imaging Camera (EPIC)

2016 ◽  
Vol 9 (4) ◽  
pp. 1785-1797 ◽  
Author(s):  
Kerry Meyer ◽  
Yuekui Yang ◽  
Steven Platnick
Keyword(s):  
Optical Thickness ◽  
Single Channel ◽  
Temperature Threshold ◽  
Retrieval Technique ◽  
Uncertainty Estimates ◽  
Imaging Camera ◽  
Cloud Temperature ◽  
Fixed Phase ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Visible Wavelengths

Abstract. This paper presents an investigation of the expected uncertainties of a single-channel cloud optical thickness (COT) retrieval technique, as well as a simple cloud-temperature-threshold-based thermodynamic phase approach, in support of the Deep Space Climate Observatory (DSCOVR) mission. DSCOVR cloud products will be derived from Earth Polychromatic Imaging Camera (EPIC) observations in the ultraviolet and visible spectra. Since EPIC is not equipped with a spectral channel in the shortwave or mid-wave infrared that is sensitive to cloud effective radius (CER), COT will be inferred from a single visible channel with the assumption of appropriate CER values for liquid and ice phase clouds. One month of Aqua MODerate-resolution Imaging Spectroradiometer (MODIS) daytime granules from April 2005 is selected for investigating cloud phase sensitivity, and a subset of these granules that has similar EPIC Sun-view geometry is selected for investigating COT uncertainties. EPIC COT retrievals are simulated with the same algorithm as the operational MODIS cloud products (MOD06), except using fixed phase-dependent CER values. Uncertainty estimates are derived by comparing the single-channel COT retrievals with the baseline bi-spectral MODIS retrievals. Results show that a single-channel COT retrieval is feasible for EPIC. For ice clouds, single-channel retrieval errors are minimal (< 2 %) due to the particle size insensitivity of the assumed ice crystal (i.e., severely roughened aggregate of hexagonal columns) scattering properties at visible wavelengths, while for liquid clouds the error is mostly limited to within 10 %, although for thin clouds (COT < 2) the error can be higher. Potential uncertainties in EPIC cloud masking and cloud temperature retrievals are not considered in this study.

scholarly journals Two-Step Root-MUSIC for Direction of Arrival Estimation without EVD/SVD Computation

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Feng-Gang Yan ◽  
Shuai Liu ◽  
Jun Wang ◽  
Ming Jin
Keyword(s):  
Super Resolution ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Low Complexity ◽  
Music Algorithm ◽  
Correlation Matrices ◽  
Noise Subspace ◽  
Using Data ◽  
Eigen Decomposition ◽  
Value Decomposition

Most popular techniques for super-resolution direction of arrival (DOA) estimation rely on an eigen-decomposition (EVD) or a singular value decomposition (SVD) computation to determine the signal/noise subspace, which is computationally expensive for real-time applications. A two-step root multiple signal classification (TS-root-MUSIC) algorithm is proposed to avoid the complex EVD/SVD computation using a uniform linear array (ULA) based on a mild assumption that the number of signals is less than half that of sensors. The ULA is divided into two subarrays, and three noise-free cross-correlation matrices are constructed using data collected by the two subarrays. A low-complexity linear operation is derived to obtain a rough noise subspace for a first-step DOA estimate. The performance is further enhanced in the second step by using the first-step result to renew the previous estimated noise subspace with a slightly increased complexity. The new technique can provide close root mean square error (RMSE) performance to root-MUSIC with reduced computational burden, which are verified by numerical simulations.

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