Mr. Roland Jonsson Profile

Roland Jonsson

at Saab Microwave Systems AB

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Publications (5)

Proceedings Article | 19 May 2005 Paper

Regularization based super resolution imaging using FFT:s

Roland Jonsson

Proceedings Volume 5808, (2005) https://doi.org/10.1117/12.604347

KEYWORDS: Super resolution, Seaborgium, Detection and tracking algorithms, Imaging systems, Synthetic aperture radar, Image processing, Image resolution, Image enhancement, Algorithm development, Expectation maximization algorithms

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Proceedings Article | 12 September 2003 Paper

Difficulties in the interpretation of synthetic aperture images of targets

Roland Jonsson, Tomas Stanek, Fredrik Dicander

Proceedings Volume 5095, (2003) https://doi.org/10.1117/12.488272

KEYWORDS: Radar, Super resolution, Optical spheres, Imaging systems, Scattering, Sensors, Calibration, Fourier transforms, Inverse problems, Signal processing

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In this paper we raise some questions about the nature and consequences of the signal model underlying SAR/ISAR imaging. One here describe a target with an object function defined over space. The measurements from a sensor is described by some other function, that are related to the object function by an operator that describe the sensor. Imaging is then the inverse problem of finding an approximation to the object function, i.e. the image, given the incomplete measurements. The usual SAR/ISAR object function is a continuous distribution of isotropic point scatterers. This distribution need to be a generalized function in order to describe the observed scattering in some cases, not only for hypothetical point scatterers, but also for a simple object such as a plate. A generalized function is of course not a true function, and there is a conceptual difficulty in viewing an image as an approximation of such an object function. A common practice is to produce calibrated images in the sense that the radar cross section of an isotropic point scatter can be directly read from the level in a magnitude-squared image. We compute such calibrated images for some simple objects such as spheres, plates and dihedrals, and show that they produce levels that not easily can be interpreted. Instead, a non trivial mix of object characteristics and imaging system characteristics such as bandwidth and aperture length influence the level at a certain image point. Even the over all appearance of the image can change. More sophisticated, "super resolving", signal processing methods postulates statistical models for the targets, and we briefly review the assumptions behind some such methods. All such methods rely on the modeling of prior information about the observed objects. This is not easy to achieve using images, which have quite a varying form even for simple objects. As an alternative, if we are prepared to leave the imaging paradigm, scattering center models give a possibility to accurately model a number of scattering phenomena. A very brief review of this promising approach is given.

Proceedings Article | 1 August 2002 Paper

Scattering center parameter estimation using a polynomial model for the amplitude aspect dependence

Roland Jonsson, Anna Gennel, David Loesaus, Fredrik Dicander

Proceedings Volume 4727, (2002) https://doi.org/10.1117/12.478695

KEYWORDS: Radar, Data modeling, Scattering, Synthetic aperture radar, Error analysis, Magnetism, Automatic target recognition, Data centers, Systems modeling, Electromagnetic scattering

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Proceedings Article | 27 August 2001 Paper

Comparison of some HRR-classification algorithms

Fredrik Dicander, Roland Jonsson

Proceedings Volume 4382, (2001) https://doi.org/10.1117/12.438202

KEYWORDS: Radar, Signal to noise ratio, Data modeling, Scattering, Calibration, Transform theory, Palladium, Target recognition, Automatic target recognition, Performance modeling

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Proceedings Article | 24 August 2000 Paper

Mastering interfering scatterers in HRR data for ATR systems

Roland Jonsson, Jan Hagberg, Fredrik Dicander

Proceedings Volume 4053, (2000) https://doi.org/10.1117/12.396353

KEYWORDS: Radar, Signal to noise ratio, Data modeling, Scattering, Sensors, Thulium, Target recognition, Automatic target recognition, Data centers, Electromagnetic scattering

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