Fast and High-Precision DOA Estimation by Iterative Interpolation on Spatial Fourier Coefficients

2018 ◽  
pp. 1530-1537
Author(s):  
Yifei Liu ◽  
Jun Zhu ◽  
Kaili Jiang ◽  
Bin Tang
Keyword(s):  
High Precision ◽  
Fourier Coefficients ◽  
Doa Estimation ◽  
Iterative Interpolation

scholarly journals Increasing Utilization of Redundant Virtual Array for DOA Estimation Based on Coprime Array

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Chenghong Zhan ◽  
Guoping Hu ◽  
Zixin Zhang ◽  
Ziang Feng
Keyword(s):  
Parameter Estimation ◽  
High Precision ◽  
Degrees Of Freedom ◽  
Doa Estimation ◽  
Far Field ◽  
Virtual Array ◽  
Previous Algorithm ◽  
Array Structure ◽  
Simulation Results ◽  
Coprime Array

In this paper, we initiated a method to estimate the direction of arrival (DOA) of far-field, narrowband, and incoherent targets using coprime array. First, we proposed a coprime array structure and analysed the distribution of difference coarray (DCA). The degrees of freedom (DOF) of the proposed coprime array became clearer by referring to the DCA conception. However, previous algorithm only uses the continuous virtual array, which causes the virtual array elements in the repeated position being abandoned. Therefore, the paper analyses the distribution of virtual array based on DCA conception and averages the receiving signal on these redundant virtual array elements to increase the utilization of receiving data. As a result, the algorithm has high precision in parameter estimation. Simulation results have shown the superiority of the proposed algorithm.

scholarly journals High Precision Sparse Reconstruction Scheme for Multiple Radar Mainlobe Jammings

Electronics ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. 1224
Author(s):  
Yuan Cheng ◽  
Daiyin Zhu ◽  
Jindong Zhang
Keyword(s):  
High Precision ◽  
Traditional Method ◽  
Bayesian Learning ◽  
Estimation Error ◽  
Doa Estimation ◽  
Sparse Reconstruction ◽  
Sparse Bayesian Learning ◽  
Oblique Projection ◽  
Direction Estimation ◽  
Reconstruction Scheme

Radar mainlobe jamming has attracted considerable attention in the field of electronic countermeasures. When the direction of arrival (DOA) of jamming is close to that of the target, the conventional antijamming methods are ineffective. Generally, mainlobe antijamming method based on blind source separation (BSS) can deteriorate the target direction estimation. Thus in this paper, a high precision sparse reconstruction scheme for multiple radar mainlobe jammings is proposed that does not suffer from failure or performance degradation inherent in the traditional method. First, the mainlobe jamming signal and desired signal components are extracted by using the joint approximation diagonalization of eigenmatrices (JADE) method. Then, oblique projection with sparse Bayesian learning (OP-SBL) method is employed to reconstruct the target with high precision. The proposed method is capable of suppressing at most three radar mainlobe jammers adaptively and also obtain DOA estimation error less than 0.1°. Simulation and experimental results confirm the effectiveness of the proposed method.

A high-precision 2D DOA estimation algorithm by a large-space three-parallel array for reducing mutual coupling

2021 ◽  
pp. 103336
Author(s):  
Sheng Liu ◽  
Jing Zhao ◽  
Decheng Wu ◽  
Hailin Cao ◽  
Zhi Mao ◽  
...  
Keyword(s):  
High Precision ◽  
Mutual Coupling ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Large Space ◽  
Parallel Array ◽  
2D Doa Estimation

Automatic measurement of SAED patterns from asbestos minerals

1988 ◽  
Vol 46 ◽  
pp. 846-847
Author(s):  
J. C. Russ ◽  
T. Taguchi ◽  
P. M. Peters ◽  
E. Chatfield ◽  
J. C. Russ ◽  
...  
Keyword(s):  
Diffraction Pattern ◽  
High Precision ◽  
Diffraction Data ◽  
Automatic Measurement ◽  
Automatic Method ◽  
Important Method ◽  
X Ray ◽  
Integrated Intensity ◽  
Asbestiform Minerals ◽  
True Center

Conventional SAD patterns as obtained in the TEM present difficulties for identification of materials such as asbestiform minerals, although diffraction data is considered to be an important method for making this purpose. The preferred orientation of the fibers and the spotty patterns that are obtained do not readily lend themselves to measurement of the integrated intensity values for each d-spacing, and even the d-spacings may be hard to determine precisely because the true center location for the broken rings requires estimation. We have implemented an automatic method for diffraction pattern measurement to overcome these problems. It automatically locates the center of patterns with high precision, measures the radius of each ring of spots in the pattern, and integrates the density of spots in that ring. The resulting spectrum of intensity vs. radius is then used just as a conventional X-ray diffractometer scan would be, to locate peaks and produce a list of d,I values suitable for search/match comparison to known or expected phases.

On effects of non-systematic reflections on weak-beam images of partial dislocations

1991 ◽  
Vol 49 ◽  
pp. 688-689
Author(s):  
K. Z. Botros ◽  
S. S. Sheinin
Keyword(s):  
High Precision ◽  
Stacking Fault ◽  
Important Application ◽  
Stacking Fault Energy ◽  
Sharp Peak ◽  
Weak Beam ◽  
Partial Dislocations ◽  
Deviation Parameter ◽  
Beam Diffraction

The main features of weak beam images of dislocations were first described by Cockayne et al. using calculations of intensity profiles based on the kinematical and two beam dynamical theories. The feature of weak beam images which is of particular interest in this investigation is that intensity profiles exhibit a sharp peak located at a position very close to the position of the dislocation in the crystal. This property of weak beam images of dislocations has an important application in the determination of stacking fault energy of crystals. This can easily be done since the separation of the partial dislocations bounding a stacking fault ribbon can be measured with high precision, assuming of course that the weak beam relationship between the positions of the image and the dislocation is valid. In order to carry out measurements such as these in practice the specimen must be tilted to "good" weak beam diffraction conditions, which implies utilizing high values of the deviation parameter Sg.

Digital differential hysteresis iimage processing displays what the microscope acquires but the eye can't see

1995 ◽  
Vol 53 ◽  
pp. 642-643
Author(s):  
Klaus-Ruediger Peters
Keyword(s):  
Image Processing ◽  
Visual System ◽  
High Precision ◽  
Image Data ◽  
Processing Technology ◽  
Output Data ◽  
Contrast Resolution ◽  
Pixel Intensity ◽  
Data Reading ◽  
Hysteresis Properties

Differential hysteresis processing is a new image processing technology that provides a tool for the display of image data information at any level of differential contrast resolution. This includes the maximum contrast resolution of the acquisition system which may be 1,000-times higher than that of the visual system (16 bit versus 6 bit). All microscopes acquire high precision contrasts at a level of <0.01-25% of the acquisition range in 16-bit - 8-bit data, but these contrasts are mostly invisible or only partially visible even in conventionally enhanced images. The processing principle of the differential hysteresis tool is based on hysteresis properties of intensity variations within an image.Differential hysteresis image processing moves a cursor of selected intensity range (hysteresis range) along lines through the image data reading each successive pixel intensity. The midpoint of the cursor provides the output data. If the intensity value of the following pixel falls outside of the actual cursor endpoint values, then the cursor follows the data either with its top or with its bottom, but if the pixels' intensity value falls within the cursor range, then the cursor maintains its intensity value.

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