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Alves, D. I., Palm, B., Pettersson, M., Vu, V. T., Machado, R., Uchoa-Filho, B. F., . . . Hellsten, H. (2020). A Statistical Analysis for Wavelength-Resolution SAR Image Stacks. IEEE Geoscience and Remote Sensing Letters, 17(2), 227-231
Open this publication in new window or tab >>A Statistical Analysis for Wavelength-Resolution SAR Image Stacks
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2020 (English)In: IEEE Geoscience and Remote Sensing Letters, ISSN 1545-598X, E-ISSN 1558-0571, Vol. 17, no 2, p. 227-231Article in journal (Refereed) Published
Abstract [en]

This letter presents a clutter statistical analysis for stacks of wavelength-resolution synthetic aperture radar (SAR) images. Each image stack consists of SAR images generated by the same sensor, using the same flight track illuminating the same scene but with a time separation between the illuminations. We test three candidate statistical distributions for time changes in the stack, namely, Rician, Rayleigh, and log-normal. The tests results reveal that the Rician distribution is a very good candidate for modeling stack of wavelength-resolution SAR images, where 98.59 & x0025; of the tested samples passed the Anderson-Darling (AD) goodness-of-fit test. Also, it is observed that the presence of changes in the ground scene is related to the tested samples that have failed in the AD test for the Rician distribution hypothesis.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2020
Keywords
Synthetic aperture radar, Radar polarimetry, Image resolution, Data models, Statistical analysis, Rician channels, Geometry, Anderson-Darling (AD) test, CARABAS II, change detection, image stack, multitemporal synthetic aperture radar (SAR) images, SAR
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering Remote Sensing
Identifiers
urn:nbn:se:bth-19226 (URN)10.1109/LGRS.2019.2917627 (DOI)000510900300009 ()
Available from: 2020-02-20 Created: 2020-02-20 Last updated: 2020-02-20Bibliographically approved
Vu, V. T., Alves, D., Palm, B., Pettersson, M., Dammert, P. & Hellsten, H. (2019). A detector for wavelength resolution SAR incoherent change detection. In: 2019 IEEE Radar Conference, RadarConf 2019: . Paper presented at IEEE Radar Conference, RadarConf, Boston, 22 April through 26 April 2019. Institute of Electrical and Electronics Engineers Inc., Article ID 8835574.
Open this publication in new window or tab >>A detector for wavelength resolution SAR incoherent change detection
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2019 (English)In: 2019 IEEE Radar Conference, RadarConf 2019, Institute of Electrical and Electronics Engineers Inc. , 2019, article id 8835574Conference paper, Published paper (Refereed)
Abstract [en]

This paper introduces an effective detector for wavelength-resolution SAR incoherent change detection. The detector is derived from Bayes' theorem. The input of the detector is the differences between surveillance and reference magnitude images simply obtained by a subtraction while the output is a summary of the detected changes. The proposed detector is tested with 24 CARABAS images that were obtained from the measurement campaign in northern Sweden in 2002. The testing results show that the detector can provide a high average detection probability, e.g., about 96%, with a very low false alarm rate, e.g., only 0.35 per square kilometer. © 2019 IEEE.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2019
Keywords
Radar imaging, Bayes' theorem, CARABAS, Change detection, Detection probabilities, False alarm rate, Measurement campaign, Northern sweden, Wavelength resolution, Synthetic aperture radar
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:bth-18815 (URN)10.1109/RADAR.2019.8835574 (DOI)2-s2.0-85073100690 (Scopus ID)9781728116792 (ISBN)
Conference
IEEE Radar Conference, RadarConf, Boston, 22 April through 26 April 2019
Available from: 2019-10-31 Created: 2019-10-31 Last updated: 2019-10-31Bibliographically approved
Vu, V. T., Gomes, N. R., Pettersson, M., Dämmert, P. & Hellsten, H. (2019). Bivariate Gamma Distribution for Wavelength-Resolution SAR Change Detection. IEEE Transactions on Geoscience and Remote Sensing, 57(1), 473-481
Open this publication in new window or tab >>Bivariate Gamma Distribution for Wavelength-Resolution SAR Change Detection
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2019 (English)In: IEEE Transactions on Geoscience and Remote Sensing, ISSN 0196-2892, E-ISSN 1558-0644, Vol. 57, no 1, p. 473-481Article in journal (Refereed) Published
Abstract [en]

A gamma probability density function (pdf) is shown to be an alternative to model the distribution of the magnitudes of high-resolution, i.e., wavelength-resolution, synthetic aperture radar (SAR) images. As investigated in this paper, it is more appropriate and more realistic statistical in comparison with, e.g., Rayleigh. A bivariate gamma pdf is considered for developing a statistical hypothesis test for wavelength-resolution incoherent SAR change detection. The practical issues in implementation of statistical hypothesis test, such as assumptions on target magnitudes, estimations for scale and shape parameters, and implementation of modified Bessel function, are addressed. This paper also proposes a simple processing scheme for incoherent change detection to validate the proposed statistical hypothesis test. The proposal was experimented with 24 CARABAS data sets. With an average detection probability of 96%, the false alarm rate is only 0.47 per square kilometer. IEEE

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2019
Keywords
Bivariate gamma, CARABAS, change detection, synthetic aperture radar (SAR)., Probability density function, Probability distributions, Radar imaging, Statistical tests, Tracking radar, Bivariate, Bivariate gamma distribution, Probability density function (pdf), Scale and shape parameters, Statistical hypothesis test, Synthetic aperture radar (SAR) images, Synthetic aperture radar
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:bth-16936 (URN)10.1109/TGRS.2018.2856926 (DOI)000455089000036 ()2-s2.0-85051396922 (Scopus ID)
Available from: 2018-08-24 Created: 2018-08-24 Last updated: 2019-01-28Bibliographically approved
Gomes, N. R., Dammert, P., Pettersson, M., Vu, V. T. & Hellsten, H. (2019). Comparison of the Rayleigh and K-Distributions for Application in Incoherent Change Detection. IEEE Geoscience and Remote Sensing Letters, 16, 756-760
Open this publication in new window or tab >>Comparison of the Rayleigh and K-Distributions for Application in Incoherent Change Detection
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2019 (English)In: IEEE Geoscience and Remote Sensing Letters, ISSN 1545-598X, E-ISSN 1558-0571, Vol. 16, p. 756-760Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
IEEE, 2019
Keywords
Change detection, likelihood ratio test, synthetic aperture radar (SAR).
National Category
Signal Processing
Identifiers
urn:nbn:se:bth-17863 (URN)10.1109/LGRS.2018.2881733 (DOI)000466228400019 ()
Available from: 2019-04-30 Created: 2019-04-30 Last updated: 2019-06-14Bibliographically approved
Ludwig Barbosa, V., Sievert, T., Rasch, J., Carlström, A., Pettersson, M. & Vu, V. T. (2019). Evaluation of Ionospheric Scintillation in GNSS Radio Occultation Measurements and Simulations. Radio Science
Open this publication in new window or tab >>Evaluation of Ionospheric Scintillation in GNSS Radio Occultation Measurements and Simulations
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2019 (English)In: Radio Science, ISSN 0048-6604, E-ISSN 1944-799XArticle in journal (Refereed) Submitted
Abstract [en]

Like any other system relying on trans-ionospheric propagation, GNSS Radio Occultation (GNSS-RO) is affected by ionospheric conditions during measurements. Regions of plasma irregularities in F-region create abrupt gradients in the distribution of ionized particles. Radio signals propagated through such regions suffer from constructive and destructive contributions in phase and amplitude, known as scintillations. Different approaches have been proposed in order to model and reproduce the wave propagation through ionospheric irregularities. We present simulations considering an one-component inverse power-law model of irregularities integrated with Multiple Phase Screen (MPS) propagation. In this work, the capability of the scintillation model to reproduce features in the signal amplitude of low latitude MetOp measurements in the early hours of DOY 76, 2015 (St. Patrick’s Day geomagnetic storm) is evaluated. Power spectral density (PSD) analysis, scintillation index, decorrelation time and standard deviation of neutral bending angle are considered in the comparison between the simulations and RO measurements. The results validate the capability of the simulator to replicate an equivalent total integrated phase variance in cases of moderate to strong scintillation.

National Category
Remote Sensing
Identifiers
urn:nbn:se:bth-18898 (URN)
Funder
Swedish National Space Board
Available from: 2019-11-11 Created: 2019-11-11 Last updated: 2019-11-18Bibliographically approved
Pettersson, M., Dahl, M., Vu, V. T. & Javadi, M. S. (2019). Future Satellite and Drone Monitoring of the Baltic‐Adriatic Corridor,Harbors, and Motorways of the Sea.
Open this publication in new window or tab >>Future Satellite and Drone Monitoring of the Baltic‐Adriatic Corridor,Harbors, and Motorways of the Sea
2019 (English)Report (Other academic)
Publisher
p. 50
National Category
Engineering and Technology
Identifiers
urn:nbn:se:bth-18575 (URN)
Projects
Tentacle
Available from: 2019-09-04 Created: 2019-09-04 Last updated: 2019-09-06Bibliographically approved
Ludwig Barbosa, V., Rasch, J., Carlström, A., Pettersson, M. & Vu, V. T. (2019). GNSS Radio Occultation Simulation Using MultiplePhase Screen Orbit Sampling. IEEE Geoscience and Remote Sensing Letters
Open this publication in new window or tab >>GNSS Radio Occultation Simulation Using MultiplePhase Screen Orbit Sampling
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2019 (English)In: IEEE Geoscience and Remote Sensing Letters, ISSN 1545-598X, E-ISSN 1558-0571Article in journal (Refereed) Epub ahead of print
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.

National Category
Remote Sensing
Identifiers
urn:nbn:se:bth-18897 (URN)10.1109/LGRS.2019.2944537 (DOI)
Projects
National Space Engineering Program (NRFP-3), grant 241/15, Swedish National Space Agency (Rymdstyrelsen)
Funder
Swedish National Space Board
Available from: 2019-11-11 Created: 2019-11-11 Last updated: 2019-11-18Bibliographically approved
Palm, B., Bayer, F., Cintra, R., Pettersson, M. & Machado, R. (2019). Rayleigh Regression Model for Ground Type Detection in SAR Imagery. IEEE Geoscience and Remote Sensing Letters, 16(10), 1660-1664, Article ID 8681168.
Open this publication in new window or tab >>Rayleigh Regression Model for Ground Type Detection in SAR Imagery
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2019 (English)In: IEEE Geoscience and Remote Sensing Letters, ISSN 1545-598X, E-ISSN 1558-0571, Vol. 16, no 10, p. 1660-1664, article id 8681168Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
IEEE, 2019
Keywords
Detection, Rayleigh distribution, regression model, reparameterized Rayleigh distribution, synthetic aperture radar (SAR) images
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:bth-17861 (URN)10.1109/LGRS.2019.2904221 (DOI)000489756100031 ()
Note

open access

Available from: 2019-04-29 Created: 2019-04-29 Last updated: 2020-01-23Bibliographically approved
Vu, V. T., Pettersson, M. & Gomes, N. R. (2019). Stability in Sar Change Detection Results Using Bivariate Rayleigh Distribution for Statistical Hypothesis Test. In: International Geoscience and Remote Sensing Symposium (IGARSS): . Paper presented at 39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS, Yokohama, 28 July 2019 through 2 August 2019 (pp. 37-40). Institute of Electrical and Electronics Engineers Inc., Article ID 8898728.
Open this publication in new window or tab >>Stability in Sar Change Detection Results Using Bivariate Rayleigh Distribution for Statistical Hypothesis Test
2019 (English)In: International Geoscience and Remote Sensing Symposium (IGARSS), Institute of Electrical and Electronics Engineers Inc. , 2019, p. 37-40, article id 8898728Conference paper, Published paper (Refereed)
Abstract [en]

A statistical hypothesis test for wavelength-resolution SAR change detection can be derived with the bivariate distributions such as Rayleigh, Gamma and K. The paper investigates the stability of change detection results obtained with a statistical hypothesis test using bivariate Rayleigh distribution. Some practical issues concerning the implementation of the statistical hypothesis test such as scale parameter estimation, target magnitude assumptions and Bessel function calculation are also addressed. The statistical hypothesis test using bi-variate Rayleigh distribution are experimented with the data set containing 24 CARABAS II images. It is shown that beside the simplicity and efficiency, a statistical hypothesis test using bivariate Rayleigh distribution can provide very stable change detection results. © 2019 IEEE.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2019
Keywords
bivariate gamma, bivariate Rayleigh, CARABAS, change detection, SAR
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:bth-19142 (URN)10.1109/IGARSS.2019.8898728 (DOI)2-s2.0-85077717158 (Scopus ID)9781538691540 (ISBN)
Conference
39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS, Yokohama, 28 July 2019 through 2 August 2019
Available from: 2020-01-23 Created: 2020-01-23 Last updated: 2020-01-23Bibliographically approved
Javadi, M. S., Dahl, M. & Pettersson, M. (2019). Vehicle speed measurement model for video-based systems. Computers & electrical engineering, 76, 238-248
Open this publication in new window or tab >>Vehicle speed measurement model for video-based systems
2019 (English)In: Computers & electrical engineering, ISSN 0045-7906, E-ISSN 1879-0755, Vol. 76, p. 238-248Article in journal (Refereed) Published
Abstract [en]

Advanced analysis of road traffic data is an essential component of today's intelligent transportation systems. This paper presents a video-based vehicle speed measurement system based on a proposed mathematical model using a movement pattern vector as an input variable. The system uses the intrusion line technique to measure the movement pattern vector with low computational complexity. Further, the mathematical model introduced to generate the pdf (probability density function) of a vehicle's speed that improves the speed estimate. As a result, the presented model provides a reliable framework with which to optically measure the speeds of passing vehicles with high accuracy. As a proof of concept, the proposed method was tested on a busy highway under realistic circumstances. The results were validated by a GPS (Global Positioning System)-equipped car and the traffic regulations at the measurement site. The experimental results are promising, with an average error of 1.77 % in challenging scenarios.

Place, publisher, year, edition, pages
Elsevier, 2019
Keywords
Intelligent transportation systems; Machine vision; Motion analysis; Pattern recognition; Speed measurement system
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:bth-17161 (URN)10.1016/j.compeleceng.2019.04.001 (DOI)000470954900019 ()
Note

open access

Available from: 2018-10-23 Created: 2018-10-23 Last updated: 2019-06-27Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-6643-312x

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