scholarly journals A-CRNN-Based Method for Coherent DOA Estimation with Unknown Source Number

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2296
Author(s):  
Yuanyuan Yao ◽  
Hong Lei ◽  
Wenjing He
Keyword(s):  
Doa Estimation ◽  
Spatial Filter ◽  
Spatial Spectrum ◽  
Data Driven ◽  
Spatial Filters ◽  
Variable Source ◽  
Matrix Reconstruction ◽  
Colored Gaussian Noise ◽  
Source Number ◽  
New Framework

Estimating directions of arrival (DOA) without knowledge of the source number is regarded as a challenging task, particularly when coherence among sources exists. Researchers have trained deep learning (DL)-based models to attack the problem of DOA estimation. However, existing DL-based methods for coherent sources do not adapt to variable source numbers or require signal independence. Herein, we put forward a new framework combining parallel DOA estimators with Toeplitz matrix reconstruction to address the problem. Each estimator is constructed by connecting a multi-label classifier to a spatial filter, which is based on convolutional-recurrent neural networks. Spatial filters divide the angle domain into several sectors, so that the following classifiers can extract the arrival directions. Assisted with Toeplitz-based method for source-number determination, pseudo or missed angles classified by the estimators will be reduced. Then, the spatial spectrum can be more accurately recovered. In addition, the proposed method is data-driven, so it is naturally immune to signal coherence. Simulation results demonstrate the predominance of the proposed method and show that the trained model is robust to imperfect circumstances such as limited snapshots, colored Gaussian noise, and array imperfections.

scholarly journals An Efficient DOA Estimation Algorithm Based on Diagonal-Symmetric Loading

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Yangyang Xie ◽  
Biao Wang ◽  
Feng Chen
Keyword(s):  
Super Resolution ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Minimum Variance ◽  
Spatial Spectrum ◽  
Estimation Accuracy ◽  
Minimum Variance Distortionless Response ◽  
Symmetric Loading ◽  
Subspace Processing ◽  
Source Number

In order to solve the problem that the subspace-like direction of arrival (DOA) estimation performs poor due to the error of sources number, this paper proposes a new super-resolution DOA estimation algorithm based on the diagonal-symmetric loading (DSL). Specifically, orthogonality principle of the minimum eigenvector of the specific covariance matrix and the source number estimation based on the improved K-means method were adopted to construct the spatial spectrum. Then, by considering the signal-to-interference-to-noise ratio (SINR), the theoretical basis for selecting parameters was given and verified by numerical experiment. To evaluate the effectiveness of the proposed algorithm, this paper compared it with the methods of minimum variance distortionless response (MVDR) and new signal subspace processing (NSSP). Experimental results prove that the proposed DSL has higher resolution and better estimation accuracy than the MVDR and NSSP.

scholarly journals Crosscorrelation and DOA Estimation for L-Shaped Array via Decoupled Atomic Norm Minimization

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yu Zhang ◽  
Yinan Sun ◽  
Gong Zhang ◽  
Xinhai Wang ◽  
Yu Tao
Keyword(s):  
Prior Information ◽  
Doa Estimation ◽  
Phase Method ◽  
Second Phase ◽  
Two Dimensional ◽  
Two Phase ◽  
Norm Minimization ◽  
Atomic Norm ◽  
Matrix Reconstruction ◽  
Source Number

A novel two-phase method for two-dimensional (2D) direction-of-arrival (DOA) estimation with L-shaped array based on decoupled atomic norm minimization (DANM) is proposed in this paper. In the first phase, given the sample crosscorrelation matrix, the gridless DANM technique considering the noise and finite snapshots effects is employed to exploit the structure and sparse properties of the crosscorrelation matrix. The resulting DANM-based algorithm not only enables the crosscorrelation matrix reconstruction (CCMR) but also reconstructs the covariance matrix of the L-shaped array. Hence, sequentially, in the second phase, the conventional 2D DOA estimators for the L-shaped array can be adopted for the angle estimation. With appropriate 2D DOA estimators, the resulting proposed algorithms can not only achieve better performance but also detect more source number, compared with conventional crosscorrelation-based DOA estimators. Moreover, the proposed method, termed CCMR-DANM, not only has blind characteristic that it does not require the prior information of source numbers but also is more efficient than the existing CCMR-based counterparts. Numerical simulations demonstrate the effectiveness and outperformance of the proposed method.

Comparison of Deterministic and Linear Cosine Spatial Filtering of Transmission Electron Micrographs

1972 ◽  
Vol 30 ◽  
pp. 596-597
Author(s):  
David A. Ansley
Keyword(s):  
Spherical Aberration ◽  
Focal Length ◽  
Chromatic Aberration ◽  
Spatial Filter ◽  
Operating Conditions ◽  
Objective Lens ◽  
List Type ◽  
Spatial Filters ◽  
Transmission Electron ◽  
Wide Range

The coherence of the electron flux of a transmission electron microscope (TEM) limits the direct application of deconvolution techniques which have been used successfully on unmanned spacecraft programs. The theory assumes noncoherent illumination. Deconvolution of a TEM micrograph will, therefore, in general produce spurious detail rather than improved resolution.A primary goal of our research is to study the performance of several types of linear spatial filters as a function of specimen contrast, phase, and coherence. We have, therefore, developed a one-dimensional analysis and plotting program to simulate a wide 'range of operating conditions of the TEM, including adjustment of the:(1) Specimen amplitude, phase, and separation(2) Illumination wavelength, half-angle, and tilt(3) Objective lens focal length and aperture width(4) Spherical aberration, defocus, and chromatic aberration focus shift(5) Detector gamma, additive, and multiplicative noise constants(6) Type of spatial filter: linear cosine, linear sine, or deterministic

Spatial-frequency and orientation tuning in psychophysical end-stopping

1998 ◽  
Vol 15 (4) ◽  
pp. 585-595 ◽  
Author(s):  
CONG YU ◽  
DENNIS M. LEVI
Keyword(s):  
Spatial Frequency ◽  
Frequency Tuning ◽  
Spatial Filter ◽  
Orientation Tuning ◽  
Maximal Strength ◽  
Facilitation Effect ◽  
Spatial Filters ◽  
Spatial Frequency Tuning ◽  
Spatial Frequencies ◽  
Wide Range

A psychophysical analog to cortical receptive-field end-stopping has been demonstrated previously in spatial filters tuned to a wide range of spatial frequencies (Yu & Levi, 1997a). The current study investigated tuning characteristics in psychophysical spatial filter end-stopping. When a D6 (the sixth derivative of a Gaussian) target is masked by a center mask (placed in the putative spatial filter center), two end-zone masks (placed in the filter end-zones) reduce thresholds. This “end-stopping” effect (the reduction of masking induced by end-zone masks) was measured at various spatial frequencies and orientations of end-zone masks. End-stopping reached its maximal strength when the spatial frequency and/or orientation of the end-zone masks matched the spatial frequency and/or orientation of the target and center mask, showing spatial-frequency tuning and orientation tuning. The bandwidths of spatial-frequency and orientation tuning functions decreased with increasing target spatial frequency. At larger orientation differences, however, end-zone masks induced a secondary facilitation effect, which was maximal when the spatial frequency of end-zone masks equated the target spatial frequency. This facilitation effect might be related to certain types of contour and texture perception, such as perceptual pop-out.

scholarly journals DOA Estimation for Coprime Linear Array Based on MI-ESPRIT and Lookup Table

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 3043 ◽  
Author(s):  
Weike Zhang ◽  
Xi Chen ◽  
Kaibo Cui ◽  
Tao Xie ◽  
Naichang Yuan
Keyword(s):  
Linear Array ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Spatial Spectrum ◽  
Angle Measurement ◽  
Lookup Table ◽  
Signal Parameters ◽  
Estimation Precision ◽  
Simulation Results ◽  
The Relationship

In order to improve the angle measurement performance of a coprime linear array, this paper proposes a novel direction-of-arrival (DOA) estimation algorithm for a coprime linear array based on the multiple invariance estimation of signal parameters via rotational invariance techniques (MI-ESPRIT) and a lookup table method. The proposed algorithm does not require a spatial spectrum search and uses a lookup table to solve ambiguity, which reduces the computational complexity. To fully use the subarray elements, the DOA estimation precision is higher compared with existing algorithms. Moreover, the algorithm avoids the matching error when multiple signals exist by using the relationship between the signal subspace of two subarrays. Simulation results verify the effectiveness of the proposed algorithm.

DOA estimation based on a modified spatial spectrum

2015 ◽  
Author(s):  
Fei Huang Fei Huang ◽  
Zhuo Zhou Zhuo Zhou ◽  
Qiaozhen Zheng Qiaozhen Zheng
Keyword(s):  
Doa Estimation ◽  
Spatial Spectrum

scholarly journals The Heimdall framework for supporting characterisation of learning health systems

2018 ◽  
Vol 25 (2) ◽  
pp. 77-87 ◽  
Author(s):  
Scott McLachlan ◽  
Henry W. W. Potts ◽  
Kudakwashe Dube ◽  
Derek Buchanan ◽  
Stephen Lean ◽  
...  
Keyword(s):  
Health Systems ◽  
Patient Outcomes ◽  
Critical Mass ◽  
Data Driven ◽  
Barriers To Adoption ◽  
Ongoing Research ◽  
Type Method ◽  
Narrative Study ◽  
New Framework

BackgroundThere are many proposed benefits of using learning health systems (LHSs), including improved patient outcomes. There has been little adoption of LHS in practice due to challenges and barriers that limit adoption of new data-driven technologies in healthcare. We have identified a more fundamental explanation: the majority of developments in LHS are not identified as LHS. The absence of a unifying namespace and framework brings a lack of consistency in how LHS is identified and classified. As a result, the LHS ‘community’ is fragmented, with groups working on similar systems being unaware of each other’s work. This leads to duplication and the lack of a critical mass of researchers necessary to address barriers to adoption.ObjectiveTo find a way to support easy identification and classification of research works within the domain of LHS.MethodA qualitative meta-narrative study focusing on works that self-identified as LHS was used for two purposes. First, to find existing standard definitions and frameworks using these to create a new unifying framework. Second, seeking whether it was possible to classify those LHS solutions within the new framework.ResultsThe study found that with apparently limited awareness, all current LHS works fall within nine primary archetypes. These findings were used to develop a unifying framework for LHS to classify works as LHS, and reduce diversity and fragmentation within the domain.ConclusionsOur finding brings clarification where there has been limited awareness for LHS among researchers. We believe our framework is simple and may help researchers to classify works in the LHS domain. This framework may enable realisation of the critical mass necessary to bring more substantial collaboration and funding to LHS. Ongoing research will seek to establish the framework’s effect on the LHS domain.

scholarly journals DOA Estimation without Source Number for Cyber-Physical Interactions

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-5
Author(s):  
Jianzhong Li ◽  
Xiaobo Gu ◽  
Ruidian Zhan ◽  
Xiaoming Xiong ◽  
Yuan Liu
Keyword(s):  
A Priori ◽  
Doa Estimation ◽  
A Priori Knowledge ◽  
Second Order Statistics ◽  
Oblique Projector ◽  
Physical Interactions ◽  
Simulation Results ◽  
The Impact ◽  
The Relationship ◽  
Source Number

In this paper, a direction of arrival (DOA) estimator is proposed to improve the cyber-physical interactions, which is based on the second-order statistics without a priori knowledge of the source number. The impact of noise will firstly be eliminated. Then the relationship between the processed covariance matrix and the steering matrix is studied. By applying the elementary column transformation, an oblique projector will be designed without the source number. At last, a rooting method will be adopted to estimate the DOAs with the constructed projector. Simulation results show that the proposed method performs as well as other methods, which requires that the source number must be known.

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