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  • 1.
    Gomes, Natanael Rodrigues
    et al.
    Federal University of Santa Maria, BRA.
    Dammert, Patrik
    Saab Surveillance AB, SWE.
    Pettersson, Mats
    Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.
    Vu, Viet Thuy
    Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.
    Hellsten, Hans
    Saab Surveillance AB, SWE.
    Comparison of the Rayleigh and K-Distributions for Application in Incoherent Change Detection2019In: IEEE Geoscience and Remote Sensing Letters, ISSN 1545-598X, E-ISSN 1558-0571, Vol. 16, p. 756-760Article in journal (Refereed)
    Abstract [en]

    The aim of this letter is to compare two incoherent change-detection algorithms for target detection in low-frequency ultrawideband (UWB) synthetic aperture radar (SAR) images. The considered UWB SAR operates in the frequency range from 20 to 90 MHz. Both approaches employ a likelihood ratio test according to the Neyman–Pearson criterion. First, the bivariate Rayleigh probability distribution is used to implement the likelihood ratio test function. This distribution is well known and has been used for change-detection algorithms in low-frequency UWB SAR with good results. Aiming to minimize the false alarm rate and taking into consideration that low-frequency UWB SAR images have high resolution compared to the transmitted wavelength, the second approach implements the test by using a bivariate K-distribution. This distribution has scale and shape parameters that can be used to adjust it to the data. No filter is applied to the data set images, and the results show that with a good statistical model, it is not needed to rely on filtering the data to decrease the number of false alarms. Therefore, we can have a better tradeoff between resolution and detection performance.

  • 2.
    Kusetogullari, Hüseyin
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Yavariabdi, Amir
    Karatay University, TUR.
    Change Detection in Multispectral Landsat Images Using Multiobjective Evolutionary Algorithm2017In: IEEE Geoscience and Remote Sensing Letters, ISSN 1545-598X, E-ISSN 1558-0571, Vol. 14, no 3, p. 414-418, article id 10.1109/LGRS.2016.2645742Article in journal (Refereed)
    Abstract [en]

    In this letter, we propose a novel method for unsupervised change detection in multitemporal multispectral Landsat images using multiobjective evolutionary algorithm (MOEA). The proposed method minimizes two different objective functions using MOEA to provide tradeoff between each other. The objective functions are used for evaluating changed and unchanged regions of the difference image separately. The difference image is obtained by using the structural similarity index measure method, which provides combination of the comparisons of luminance, contrast, and structure between two images. By evolving a population of solutions in the MOEA, a set of Pareto optimal solution is estimated in a single run. To find the best solution, a Markov random field fusion approach is used. Experiments on semisynthetic and real-world data sets show the efficiency and effectiveness of the proposed method.

  • 3.
    Ludwig Barbosa, Vinícius
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.
    Rasch, Joel
    Molflow, SwWE.
    Carlström, Anders
    RUAG Space AB, SWE.
    Pettersson, Mats
    Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.
    Vu, Viet Thuy
    Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.
    GNSS Radio Occultation Simulation Using MultiplePhase Screen Orbit Sampling2019In: IEEE Geoscience and Remote Sensing Letters, ISSN 1545-598X, E-ISSN 1558-0571Article in journal (Refereed)
    Abstract [en]

    Wave optics propagators (WOPs) are commonlyused to describe the propagation of radio signals through earth’satmosphere. In radio occultation (RO) context, multiple phasescreen (MPS) method has been used to model the effects of theatmosphere in Global Navigation Satellite System (GNSS) signalsduring an occultation event. WOP implementation includes,in addition to MPS, a diffraction integral as the final step tocalculate the radio signal measured in the low-earth orbit (LEO)satellite. This approach considers vacuum as the propagationmedium at high altitudes, which is not always the case when theionosphere is taken into account in simulations. An alternativeapproach is using MPS all the way to LEO in order to samplethe GNSS signal in orbit. This approach, named MPS orbitsampling (MPS-OS), is evaluated in this letter. Different scenariosof setting occultation assuming a short segment of the LEO orbithave been simulated using MPS and MPS-OS. Results have beencompared to Abel transform references. Furthermore, a longsegment scenario has been evaluated as well. A comparison ofbending angle (BA) and residual ionospheric error (RIE) showsthe equivalence between MPS and MPS-OS results. The mainapplication of MPS-OS should be in occultation events with longsegments of orbit and including ionosphere, in which a standardWOP may not be appropriate.

  • 4.
    Palm, Bruna
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.
    Bayer, Fabio
    Universidade Federal de Santa Maria, BRA.
    Cintra, Renato
    Universidade Federal de Per nambuco, BRA.
    Pettersson, Mats
    Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.
    Machado, Renato
    Aeronautics Institute of Technology (ITA), BRA.
    Rayleigh Regression Model for Ground Type Detection in SAR Imagery2019In: IEEE Geoscience and Remote Sensing Letters, ISSN 1545-598X, E-ISSN 1558-0571, Vol. 16, no 10, p. 1660-1664Article in journal (Refereed)
    Abstract [en]

    This letter proposes a regression model for nonnegative signals. The proposed regression estimates the mean of Rayleigh distributed signals by a structure which includes a set of regressors and a link function. For the proposed model, we present: 1) parameter estimation; 2) large data record results; and 3) a detection technique. In this letter, we present closed-form expressions for the score vector and Fisher information matrix. The proposed model is submitted to extensive Monte Carlo simulations and to the measured data. The Monte Carlo simulations are used to evaluate the performance of maximum likelihood estimators. Also, an application is performed comparing the detection results of the proposed model with Gaussian-, Gamma-, and Weibull-based regression models in synthetic aperture radar (SAR) images.

  • 5.
    Renato, Machado
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.
    Vu, Viet Thuy
    Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.
    Pettersson, Mats
    Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.
    Dammert, Patrik
    Saab Electronic Defense Systems, SWE.
    Hellsten, Hans
    Saab Electronic Defense Systems, SWE.
    The stability of UWB low-frequency SAR images2016In: IEEE Geoscience and Remote Sensing Letters, ISSN 1545-598X, E-ISSN 1558-0571, Vol. 13, no 8, p. 1114-1118Article in journal (Refereed)
    Abstract [en]

    This letter presents an analysis of prefiltered clutter ultrawideband (UWB) very high frequency synthetic aperture radar (SAR) images. The image data are reorganized into subvectors based on the observation of the image-pair magnitude samples. Based on this approach, we present a statistical description of the SAR clutter obtained by the subtraction between two real SAR images. The statistical analysis based on bivariate distribution data organized into different intervals of magnitude can be an important tool to further understand the properties of the backscattered signal for low-frequency SAR images. In this letter, it is found that, for “good” image pairs, the subtracted image has Gaussian distributed clutter backscattering and that the noise mainly consists of the thermal noise and, therefore, speckle noise does not have to be considered. This is a consequence of the stable backscattering for a UWB low-frequency SAR system.

  • 6.
    Viet Thuy, Vu
    Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.
    Wavelength-resolution SAR Incoherent ChangeDetection Based on Image Stack2017In: IEEE Geoscience and Remote Sensing Letters, ISSN 1545-598X, E-ISSN 1558-0571, Vol. 14, no 7, p. 1012-1016Article in journal (Refereed)
    Abstract [en]

    This letter presents a wavelength-resolution syn-thetic aperture radar incoherentchange detection method basedon image stack, i.e., there are more than one reference or/andsurveillance image. Considering image stack in statistical hypoth-esis test for change detection is expected to result into a simplemathematical expression for implementation and provide betterchange detection results. As presented in this letter, a statisticalhypothesis test is developed on bivariate Gaussian distributionfor an image stack of two reference images and one surveillanceimage. The requirement for the image stack is three imagesassociated with three measurements with no change between twoof them. A detection method with simple processing scheme isproposed. The method is experimented with 24 CARABAS datasets. The results indicate that high average detection probability,e.g., 96%, with very low false alarm rate, e.g., only 0.19/km2,is obtained with the proposal.

  • 7.
    Vu, Viet
    et al.
    Blekinge Institute of Technology, School of Engineering, Department of Electrical Engineering.
    Sjögren, Thomas
    Blekinge Institute of Technology, School of Engineering, Department of Electrical Engineering.
    Pettersson, Mats
    Blekinge Institute of Technology, School of Engineering, Department of Electrical Engineering.
    Two-Dimensional Spectrum for BiSAR Derivation Based on Lagrange Inversion Theorem2014In: IEEE Geoscience and Remote Sensing Letters, ISSN 1545-598X, E-ISSN 1558-0571, Vol. 11, no 7, p. 1210-1214Article in journal (Refereed)
    Abstract [en]

    A 2-D spectrum for bistatic synthetic aperture radar is derived in this letter. The derivation is based on the commonly used mathematic principles such as themethod of stationary phase and the Fourier transform and the Lagrange inversion theorem in order to find the point of stationary phase in the method of stationary phase. Using the Lagrange inversion theorem allows minimizing the initial assumptions or the initial approximations. The derived 2-D spectrum is compared with the commonly used 2-D spectrum to verify it and illustrate its accuracy.

  • 8.
    Vu, Viet Thuy
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.
    Pettersson, Mats
    Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.
    Derivation of Bistatic SAR Resolution Equations Based on Backprojection2018In: IEEE Geoscience and Remote Sensing Letters, ISSN 1545-598X, E-ISSN 1558-0571, Vol. 15, no 5, p. 694-698Article in journal (Refereed)
    Abstract [en]

    This letter introduces ground-range and cross-range resolution equations for the side-looking bistatic synthetic aperture radar (SAR). The derivation is based on the backprojection integral and the method of stationary phase. The ground-range and cross-range resolution equations are provided in closed form, making them easy for calculation. They are, therefore, helpful for bistatic SAR system development. The derived ground-range and cross-range resolution equations are validated with the bistatic data simulated mainly using the parameters of the LORA system. IEEE

  • 9.
    Vu, Viet Thuy
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.
    Pettersson, Mats
    Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.
    Sjögren, Thomas
    Two-Dimensional Spectrum for BiSAR Derivation Based on Lagrange Inversion Theorem2014In: IEEE Geoscience and Remote Sensing Letters, ISSN 1545-598X, E-ISSN 1558-0571, Vol. 11, no 7, p. 1210-1214Article in journal (Refereed)
    Abstract [en]

    A 2-D spectrum for bistatic synthetic aperture radar is derived in this letter. The derivation is based on the commonly used mathematic principles such as themethod of stationary phase and the Fourier transform and the Lagrange inversion theorem in order to find the point of stationary phase in the method of stationary phase. Using the Lagrange inversion theorem allows minimizing the initial assumptions or the initial approximations. The derived 2-D spectrum is compared with the commonly

  • 10. Vu, Viet Thuy
    et al.
    Sjögren, Thomas
    Pettersson, Mats
    Ultrawideband Chirp Scaling Algorithm2010In: IEEE Geoscience and Remote Sensing Letters, ISSN 1545-598X, E-ISSN 1558-0571, Vol. 7, no 2, p. 281-185Article in journal (Refereed)
    Abstract [en]

    A new version of chirp scaling (CS), the so-called ultrawideband (UWB) CS (UCS), is proposed in this letter. UCS aims at UWB synthetic aperture radar (SAR) systems utilizing large fractional bandwidth and wide antenna beamwidth associated with a wide integration angle. Furthermore, it is also valid for SAR systems with special characteristics such as ground moving target indication SAR systems with a very high pulse repetition frequency.

  • 11. Vu, Viet Thuy
    et al.
    Sjögren, Thomas
    Pettersson, Mats
    Håkansson, Lars
    Gustavsson, Anders
    Ulander, Lars
    RFI Suppression in Ultrawideband SAR Using an Adaptive Line Enhancer2010In: IEEE Geoscience and Remote Sensing Letters, ISSN 1545-598X, E-ISSN 1558-0571, Vol. 7, no 4, p. 694-698Article in journal (Refereed)
    Abstract [en]

    In this letter, we propose an approach to suppress radio-frequency interference (RFI) in ultrawideband (UWB) low-frequency synthetic aperture radar (SAR). According to the proposal, RFI is suppressed by using an adaptive line enhancer controlled by the normalized least mean square algorithm. The approach is tested successfully on real UWB low-frequency SAR data. In order to keep the computational burden down, possible ways to integrate the RFI suppression approach into SAR imaging algorithms are also suggested.

1 - 11 of 11
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