Standard image products of Russian highly elliptical remote sensing system “Arktika-M”

Egoshkin, Nikolay; Kuznetcov, A. E.; Eremeev, V. V.; Solovyev, Valeriy; Kochergin, Andrei

doi:10.1117/12.2325099

Cited by 2 publications

(4 citation statements)

References 1 publication

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“…Lemma 5. The inverse problem of restoring the desired solution w(ξ, η) (defocus elimination problem) is reduced by solving the two-dimensional Fredholm integral equation (IE) of the first kind (7) using the stable method of parametric Wiener filtering (PWF) [5,[8][9][10][11]15,23] (cf. ( 6)):…”

Section: Lemmamentioning

confidence: 99%

“…To determine the parameter ∆ (the smear magnitude), we mark the frequency ω 1 and the Nyquist frequency ω max , the first and last zeros of the function |G(ω, 0)|, on the ω-axis in Figure 1a. According to (15), the parameter ∆ will be equal to:…”

Section: Determining the Image Smear Parametersmentioning

confidence: 99%

“…IRDs can be installed both permanently on a stationary base and moving objects, such as cars, airplanes, unmanned aerial vehicles, and satellites, and allow the viewing of various environments (see, for example, [1] (pp. [12][13][14][15][16][17][18][19]). However, the images often have resections (damages, distortions); namely, smearing (diffusing) due to the object shifting during an exposure, defocusing (out of focus) because of setting the focus incorrectly, noise caused by external (atmospheric) or internal (instrumental) factors, the Gibbs effect, and others.…”

Section: Introductionmentioning

confidence: 99%

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“Spectral Method” for Determining a Kernel of the Fredholm Integral Equation of the First Kind of Convolution Type and Suppressing the Gibbs Effect

Sizikov,

Rushchenko

2023

Mathematics

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A set of one-dimensional (as well as one two-dimensional) Fredholm integral equations (IEs) of the first kind of convolution type is solved. The task for solving these equations is ill-posed (first of all, unstable); therefore, the Wiener parametric filtering method (WPFM) and the Tikhonov regularization method (TRM) are used to solve them. The variant is considered when a kernel of the integral equation (IE) is unknown or known inaccurately, which generates a significant error in the solution of IE. The so-called “spectral method” is being developed to determine the kernel of an integral equation based on the Fourier spectrum, which leads to a decrease of the error in solving the IE and image improvement. Moreover, the authors also propose a method for diffusing the solution edges to suppress the possible Gibbs effect (ringing-type distortions). As applications, the problems for processing distorted (smeared, defocused, noisy, and with the Gibbs effect) images are considered. Numerical examples are given to illustrate the use of the “spectral method” to enhance the accuracy and stability of processing distorted images through their mathematical and computer processing.

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Section: Lemmamentioning

confidence: 99%

Section: Determining the Image Smear Parametersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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“Spectral Method” for Determining a Kernel of the Fredholm Integral Equation of the First Kind of Convolution Type and Suppressing the Gibbs Effect

Sizikov,

Rushchenko

2023

Mathematics

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“…The author of these works uses ideal azimuth and elevation angles as initial data without taking into account the instrumental error in their measurements, which leads to inaccuracies in calculating the geographic coordinates of ground objects, especially at large distances relative to the UAV. Also, the disadvantage of this approach is the impossibility of taking into account the errors in determining the satellite coordinates of the UAV associated with the shift in the coordinates of the satellite or the clock of the receiver and the satellite [10,11].…”

Section: обработка информации и управлениеmentioning

confidence: 99%

Method and algorithm for determining the geographic coordinates of ground objects from an unmanned aerial vehicle

Parfiryev

Parfiryeva

Душкин

2021

ICS

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Introduction: As practice shows, the accuracy of determining the coordinates of objects is influenced by many factors associated with the presence of errors in measuring the angular coordinates of the optical system, the distance to the object and the presence of an inhomogeneous terrain. Purpose: Improving the accuracy of determining the geographic coordinates of ground objects from an unmanned aerial vehicle. Results: A method and an algorithm for determining geographic coordinates based on the use of a digital terrain model and optimization methods have been developed. The accuracy of calculating the coordinates of the object is increased by minimizing the error in measuring the declination angle, azimuth to the target and slant range. To confirm the analytical calculations, a field experiment was carried out with a car on the ground. At a considerable distance, at which the slant range was 900 m, several data freeze frames were taken. As a result of calculations, the geographical coordinates of the car were obtained in two ways (traditional and developed). Ultimately, the accuracy of calculating coordinates using the developed method is 4.8 times higher. Practical relevance: The method and algorithms for information processing proposed in the work will make it possible to create a number of hardware and software solutions for guidance and target designation systems.

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Standard image products of Russian highly elliptical remote sensing system “Arktika-M”

Cited by 2 publications

References 1 publication

“Spectral Method” for Determining a Kernel of the Fredholm Integral Equation of the First Kind of Convolution Type and Suppressing the Gibbs Effect

“Spectral Method” for Determining a Kernel of the Fredholm Integral Equation of the First Kind of Convolution Type and Suppressing the Gibbs Effect

Method and algorithm for determining the geographic coordinates of ground objects from an unmanned aerial vehicle

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