Algorithms for automatic detection and recognition of low contrast radar objects using noise-like broadband signals

2021 ◽  
Author(s):  
E.V. Egorova ◽  
A.N. Ribakov ◽  
M.Kh. Aksayitov
Keyword(s):  
Spectral Methods ◽  
Block Diagram ◽  
A Priori ◽  
Original Method ◽  
Optimal Algorithms ◽  
A Priori Information ◽  
Low Contrast ◽  
Priori Information ◽  
Detection And Recognition

An algorithm for automatic detection and recognition of low-contrast ground targets using noise-like broadband signals and the use of combined processing of radar signals against the background of interference is presented; the proposed original method for processing signals from airborne objects during their detection and determination of their coordinates synthesizes optimal algorithms for detecting radar objects in the case of a priori information about useful signals and interference, as well as the ability to determine the range and speed of movement; the block diagram of the mathematical model of signal processing is considered on the basis of the developed algorithms for identifying stationary targets against the background of local objects by the radar portrait, as well as by the envelope of the radar signal; the results of testing mathematical modeling of the algorithm for recognizing signals from stationary targets and a forest with an equal probability of the appearance of these targets in the analyzed space are presented. The results of domestic theoretical and experimental research today characterize the main areas of research in the field of detection and recognition of various radar objects. The main research tool of most works is the search and development of promising mathematical models of objects and the modeling of secondary radiation for their recognition, which in some cases allows obtaining additional information about these objects. Correlation and spectral methods of their processing are currently being considered in relation to the noise sounding signal of a radar station. This article analyzes the application of correlation and spectral methods in processing noise signals with the identification of the disadvantages and advantages of each of the methods; the functioning of the block diagram of the known single-channel noise radar stations with sequential spectral processing of the total signal is considered. The proposed original method for processing signals from airborne objects during their detection and determination of their coordinates synthesizes optimal algorithms for detecting targets in the case of a priori information about useful signals and interference, as well as the ability to determine the distance and speed of movement. It should be noted the promising application of combined processing of radar signals against the background of interference, taking into account simultaneously the spatial, polarization, temporal and frequency features of the signals reflected from objects. With regard to the problem of recognizing the shape of objects, both in Russia and abroad, intensive work is being carried out to improve the resolution of on-board radars with a synthesized broadband antenna array, while raising the range resolution and increasing the angular resolution allow obtaining long-range portraits of these objects, as well as seeing them. elements and obtain images of targets. In the study of methods for detecting radar objects based on Gaussian noise signals with a large base, it is shown that such signals are promising for detecting subtle objects at ranges greater than with conventional monopulse radar. When receiving noise signals with a large base, spectral methods of signal extraction turn out to be more advantageous in comparison with the known correlation method of signal processing. Based on the use of noise signals, recognition of ground and air objects is realized, while the method of long-range portraits can have an advantage over the envelope method. Based on the results of mathematical modeling, the possibility of automatic recognition of stationary ground objects by two different methods was confirmed with a high probability of their recognition.

Using a Priori Information in Energy-Dispersive X-Ray Fluorescence Analysis of Complex Samples

1991 ◽  
Vol 35 (B) ◽  
pp. 1205-1209
Author(s):  
I. A. Kondurov ◽  
P. A. Sushkov ◽  
T. M. Tjukavina ◽  
G. I. Shulyak
Keyword(s):  
High Temperature Superconductors ◽  
A Priori ◽  
Fluorescence Analysis ◽  
A Priori Information ◽  
Complex Samples ◽  
X Ray ◽  
Edxrf Analysis ◽  
The Matrix ◽  
Priori Information

In multielement EDXRF analysis of very complex unknowns, some problems in data evaluation may be simplified if one can take into account a priori information on the properties of the incident and detected radiations, and also available data on the matrix of the sample. The number of variables can be drastically shortened in the LSM procedures in this case. One of the best examples of complex unknowns is the determination of the rare earth element content of ores, and most recently in samples of high temperature superconductors (HiTc).

Defect Structure Analysis in Semiconductors by HREM and New Compatible Techniques

1984 ◽  
Vol 42 ◽  
pp. 364-367
Author(s):  
J.C.H. Spence
Keyword(s):  
A Priori ◽  
Heavy Atom ◽  
A Priori Information ◽  
Atomic Column ◽  
Structure Information ◽  
Semiconductor Defects ◽  
Semiconductor Interfaces ◽  
Priori Information ◽  
Similar Unit

The determination of atomic co-ordinates from HREM images has greatly improved our understanding of semiconductor defects, but chemical and electronic structure information are also needed. Thus suitable HREM compatible techniques must be developed and this article reviews some of these.The intimate relationship between resolution and noise has been exploited for many years in biological HREM. Since the centre of a very broad gaussion peak can be found with an accuracy which depends mainly on noise, heavy atom positions in inorganic crystals can be determined from HREM images with an accuracy of ±0.1Å (well beyond the information and point resolution limits of an HREM image) by the addition of similar unit cell images. This method makes extensive use of a-priori information (that there is only one atomic column rather than an unresolved pair, other atom co-ordinates, symmetry) and fails for isolated defects, but may be useful for semiconductor interfaces and surfaces.

Substantiation of selection and dimension reduction of non-centered informative features of signals in information systems of short-range location

2021 ◽  
Author(s):  
V.K. Khokhlov ◽  
V.V. Glazkov ◽  
A.K. Likhoedenko
Keyword(s):  
Dimension Reduction ◽  
Short Range ◽  
A Priori ◽  
Regression Coefficients ◽  
A Priori Information ◽  
Network Algorithms ◽  
Informative Parameters ◽  
Regression Algorithms ◽  
Priori Information ◽  
Detection And Recognition

In this paper, we consider the issues of selection of informative features, dimension reduction of feature vectors in regression algorithms of detection and recognition of signals and interference, as well as the issues of obtaining informative features using neural network algorithms with ill-conditioned data. The problem is considered in relation to the short-range location, with large dynamic ranges of informative features and small decision intervals, when it is impossible to estimate mathematical expectations, that is, it is impossible to use adaptive algorithms. Regression algorithms for processing non-centered random signals are presented, with a priori unknown mathematical expectations of informative parameters, which consider the specificity of short-range location and use a priori information about the initial regression characteristics of informative features – multiple initial regression coefficients. Unlike it is in traditional regression analysis, the coefficients are determined through the elements of the matrices that are inverse to the matrices of the initial correlation moments. In regression algorithms, it is necessary to calculate the square error of multiple initial regression representations. The residual mean of squares of the initial regression representations are used to justify the methods for selection and dimension reduction of informative features of signals in the problems of detection and recognition of signals and interference. We give examples of application of the proposed methods for the problems of detection and recognition of a helicopter and airplane by acoustic signals when processing histograms of the distributions of the durations of intervals between zeros, samples of envelopes and samples of local extrema of the power spectral density. Good separability of the {airplane} and {helicopter} classes in the space of non-centered parameters of signals (features) is shown. The issue of obtaining regression statistical characteristics with illconditioned data is considered. If the matrices of the correlation moments of the informative features of signals and noise are illconditioned, it becomes impossible to obtain a priori information about the multiple initial regression coefficients. The possibility of using neural network algorithms to obtain estimates of the residual mean squares of regression representations and multiple initial regression coefficients through the weight coefficients on the inputs of neurons with ill-conditioned data is shown. The results can be used in short-range location systems with a large dynamic range of non-centered informative parameters, when it is not possible to estimate the mathematical expectations of the signal parameters due to the limited observation interval.

scholarly journals Statistical Ranging of Orbits for Trans-Neptunian Objects

2002 ◽  
Vol 12 ◽  
pp. 255-256 ◽  
Author(s):  
J. Virtanen ◽  
K. Muinonen ◽  
E. Bowell
Keyword(s):  
Phase Space ◽  
A Priori ◽  
Posteriori Probability ◽  
A Posteriori ◽  
A Priori Information ◽  
A Posteriori Probability ◽  
Uncertainty Prediction ◽  
Absolute Magnitudes ◽  
Priori Information

AbstractWe consider initial determination of orbits for trans-neptunian objects (TNOs), a topical theme because of the rapidly growing TNO population and the challenges in recovering lost TNOs. We apply the method of initial phase-space ranging of orbits to the poorly observed TNOs. The rigorous a posteriori probability density of the TNO orbital elements is examined using a Monte Carlo technique by varying the TNO topocentric ranges corresponding to the observation dates. We can optionally adopt a Bayesian approach to select the region of phase space containing the most plausible orbits. This is accomplished by incorporating semimajor axes, eccentricities, inclinations, and absolute magnitudes of multi-apparition TNOs as a priori information. The resulting a posteriori distributions permit ephemeris and ephemeris uncertainty prediction for TNO recovery observations.

scholarly journals Determination of the barycentric velocity of an astrometric satellite using its own observational data

2007 ◽  
Vol 3 (S248) ◽  
pp. 252-255 ◽  
Author(s):  
A. G. Butkevich ◽  
S. A. Klioner
Keyword(s):  
Observational Data ◽  
A Priori ◽  
Translational Motion ◽  
Orbital Velocity ◽  
A Priori Information ◽  
Proposed Model ◽  
Velocity Constraints ◽  
Priori Information ◽  
Astrometric Data

AbstractThe problem of determination of the orbital velocity of an astrometric satellite from its own observational data is studied. It is well known that data processing of microarcsecond-level astrometric observations imposes very stringent requirements on the accuracy of the orbital velocity of satellite (a velocity correction of 1.45 mm/s implies an aberrational correction of 1 μas). Because of a number of degeneracies the orbital velocity cannot be fully restored from observations provided by the satellite. Seven constraints that must be applied on a velocity parameterization are discussed and formulated mathematically. It is shown what part of velocity can be recovered from astrometric data using a combined fit of both velocity parameters and astrometric parameters of the sources. Numerical simulations show that, with the seven constraints applied, the velocity and astrometric parameters can be reliably estimated from observational data. It is also argued that the idea to improve the velocity of an astrometric satellite from its own observational data is only useful if a priori information on orbital velocity justifies the applicability of the velocity constraints. The proposed model takes into account only translational motion of the satellite and ignores any satellite-specific parameters. Therefore, the results of this study are equally applicable to both scanning missions similar to Gaia, and pointing ones like SIM, provided that enough sources were observed sufficiently uniformly.

scholarly journals Increase the contrast of the image of objects in the active optoelectronic system with dynamic spectral processing of optical emitting

2020 ◽  
Vol 3 (59) ◽  
pp. 122-126
Author(s):  
O. Cherkashyna
Keyword(s):  
Light Emission ◽  
Block Diagram ◽  
A Priori ◽  
Spectral Characteristics ◽  
Optical Signal ◽  
Matched Filtering ◽  
A Priori Information ◽  
Spectral Processing ◽  
Optoelectronic System ◽  
Priori Information

The article discusses a method for increasing the contrast of images in an optoelectronic system based on active dynamic spectral matched filtering. The principles of constructing active optoelectronic systems with matched filtering are based on the fact that the optical system uses a set of amplitude-controlled radiation sources operating in different parts of the spectral range as emitting sources. It is essential that the energy composition of the light emission control signals is formed on the basis of a priori information about the characteristics of the target and the background, so as to reduce the value of the spectral components of the optical signal reflected from the surface belongs to the background and with minimal attenuation of the signal intensity belonging to the object. The method assumes the presence of a set of a priori information about the spectral characteristics of the background and the object to form the instrumental function for controlling the amplitude of emitting sources. The analysis of the mathematical and physical aspects of systems with dynamic spectral processing of active type optical emitting is made. It is shown that an active optoelectronic system with dynamic spectral processing can be considered as an analog processor for calculating the dot product of a vector by a vector. One of the factors is the reflection coefficient from a surface with a priori known characteristics, and the second is a dimmable multispectral signal. A block diagram of an optoelectronic system with dynamic spectral processing of optical emitting with active formation of the information field in order to increase the contrast of the object image has been developed. The goal of the article is to develop the mathematical and physical foundations for constructing an active optoelectronic system with dynamic spectral processing of optical emitting in order to increase the image contrast.

scholarly journals INVERSION OF INTERVAL VELOCITIES: APPLICATION TO A GEOLOGICAL MODEL FROM A PRE-SALT AREA

2015 ◽  
Vol 33 (1) ◽  
pp. 19
Author(s):  
Thais Gomes Santana ◽  
Amin Bassrei
Keyword(s):  
Singular Value Decomposition ◽  
Relative Entropy ◽  
A Priori ◽  
Singular Value ◽  
A Priori Information ◽  
Minimum Relative Entropy ◽  
Priori Information ◽  
Interval Velocities ◽  
Value Decomposition

ABSTRACT. Seismic methods study the propagation of elastic wave fields inside the Earth, with the goal to provide subsurface images. In this work, the determination of the time interval velocity distribution is the main information provided. Several synthetic models were used, where one is based in a real situation, a dip section from the pre-salt region, central part of the Santos Basin, Brazil. Themethods used to determine interval velocities were based on the Dix transform, singular value decomposition (SVD) and minimum relative entropy (MRE). Dix transform showed excellent results when used in simple geological models, and was coincident to the other two methods. With the addition of a priori information, the SVD and MRE showed to be good methods for the determination of the interval velocities. When comparing SVD and MRE methods the latter showed the best results. When the a priori information is constant, the SVD and MRE methods give the same velocity estimate given from the direct application of the Dix transform.Keywords: inversion of interval velocities, singular value decomposition, minimum relative entropy, pre-salt.RESUMO. Os métodos sísmicos utilizam o campo de propagação de ondas elásticas no interior da Terra, com o objetivo de fornecer imagens da subsuperfície. Neste trabalho, a determinação do campo de velocidades intervalares é a principal informação a ser fornecida. Foram utilizados modelos sintéticos, sendo um deles baseado em uma situação real, no caso uma sessão dip , na região do pré-sal, parte central da Bacia de Santos. Os métodos usados para determinar as velocidades intervalares foram a transformada de Dix, a decomposição por valores singulares (SVD) e a entropia relativa mínima (MRE). A transformada de Dix, quando usada em modelos geológicos mais simples apresentou excelentes resultados coincidente aos outros dois métodos. Com a adição de estimativas a priori , o SVD e o MRE se mostraram como bons métodos para a determinação das velocidades intervalares, sendo que o MRE apresentou os melhores resultados. Quando a informação a priori é constante, os métodos do SVD e MRE fornecem a mesma estimativa de velocidade que é obtida pela transformada de Dix.Palavras-chave: inversão de velocidades intervalares, decomposição por valores singulares, entropia relativa mínima, pré-sal.

DETERMINATION OF THE STACKING VELOCITY FIELD VIA OPTIMIZATION METHODS

2016 ◽  
Vol 33 (3) ◽  
Author(s):  
Danian Steinkirch de Oliveira ◽  
Milton José Porsani ◽  
Paulo Eduardo Miranda Cunha
Keyword(s):  
Genetic Algorithm ◽  
Velocity Field ◽  
A Priori ◽  
Optimization Methods ◽  
Optimization Method ◽  
A Priori Information ◽  
Algorithm Optimization ◽  
Genetic Algorithm Optimization ◽  
Priori Information

ABSTRACT. We developed a strategy for automatic Semblance panels pick, that uses Genetic Algorithm optimization method. In conjunction with restrictions and penalties set from a priori information... RESUMO. Foi desenvolvida uma estratégia de pick automático dos painéis de Semblance , que usa método de otimização Algorítmo Genético. Em conjunto com restrições...

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