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Numrering	Referens	Omslagsbild	Hitta
1.	Aldhubaib, Faisal, et al. (författare) Characteristic Polarization States in an Ultra-Wide-Band Context Based on Singularity Expansion Method 2009 Ingår i: IEEE Geoscience and Remote Sensing Letters. - 1558-0571 .- 1545-598X. ; 6:4, s. 792-796 Tidskriftsartikel (refereegranskat)
2.	Alves, Dimas I, et al. (författare) A Statistical Analysis for Wavelength-Resolution SAR Image Stacks 2020 Ingår i: IEEE Geoscience and Remote Sensing Letters. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 1545-598X .- 1558-0571. ; 17:2, s. 227-231 Tidskriftsartikel (refereegranskat)abstract 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.
3.	Alves, Dimas I., et al. (författare) Neyman-Pearson Criterion-Based Change Detection Methods for Wavelength-Resolution SAR Image Stacks 2022 Ingår i: IEEE Geoscience and Remote Sensing Letters. - : Institute of Electrical and Electronics Engineers Inc.. - 1545-598X .- 1558-0571. ; 19 Tidskriftsartikel (refereegranskat)abstract This letter presents two new change detection (CD) methods for synthetic aperture radar (SAR) image stacks based on the Neyman-Pearson criterion. The first proposed method uses the data from wavelength-resolution images stack to obtain background statistics, which are used in a hypothesis test to detect changes in a surveillance image. The second method considers a priori information about the targets to obtain the target statistics, which are used together with the previously obtained background statistics, to perform a hypothesis test to detect changes in a surveillance image. A straightforward processing scheme is presented to test the proposed CD methods. To assess the performance of both proposed methods, we considered the coherent all radio band sensing (CARABAS)-II SAR images. In particular, to obtain the temporal background statistics required by the derived methods, we used stacks with six images. The experimental results show that the proposed techniques provide a competitive performance in terms of probability of detection and false alarm rate compared with other CD methods. CCBY
4.	Askne, Jan, 1936, et al. (författare) On the Estimation of Boreal Forest Biomass From TanDEM-X Data Without Training Samples 2015 Ingår i: IEEE Geoscience and Remote Sensing Letters. - : Institute of Electrical and Electronics Engineers (IEEE). - 1558-0571 .- 1545-598X. ; 12:4, s. 771-775 Tidskriftsartikel (refereegranskat)abstract Boreal forests play an important part in the climate system, and estimates of the biomass are important also from an economic point of view. In this letter, forest aboveground biomass is estimated from bistatic TanDEM-X data, a Lidar digital elevation model (DEM), and the interferometric water cloud model, without using training samples to calibrate the model. The forest was characterized by allometric relations for area fill (vegetation fraction) and height versus stem volume, and stem volume versus biomass. Biomass was estimated for 202 forest stands at least 1 ha large at the forest test site of Remningstorp, Sweden, from 18 bistatic TanDEM-X acquisitions with a relative root-mean-square error (RMSE) of 16%-32%. TanDEM-X acquisitions with a height of ambiguity around 80 m resulted in the best results. A multitemporal combination resulted in a relative RMSE of 17%. This result is comparable with the retrieval error obtained in a previous study when training the model using a set of known forest stands.
5.	Berg, Anders, 1983, et al. (författare) SAR Algorithm for Sea Ice Concentration - Evaluation for the Baltic Sea 2012 Ingår i: IEEE Geoscience and Remote Sensing Letters. - 1558-0571 .- 1545-598X. ; 9:5, s. 938 - 942 Tidskriftsartikel (refereegranskat)abstract A new sea ice concentration algorithm has been developed for C-band synthetic aperture radar data. Detailed autocorrelation statistics are derived and adopted by the algorithm, and a neural network is utilized for training against 41 sea ice charts. The charts are produced by ice analysts at the Swedish Ice Service and cover the Baltic Sea. The classification of open water pixels is accurate to 94% on average, and the classification of sea ice pixels has an accuracy of 87%. This results in a root-mean-square error of 6.7 percentage points in estimating the sea ice concentration.
6.	Blixt, E. M., et al. (författare) Optical flow analysis of the aurora borealis 2006 Ingår i: IEEE Geoscience and Remote Sensing Letters. - : Institute of Electrical and Electronics Engineers (IEEE). - 1545-598X .- 1558-0571. ; 3:1, s. 159-163 Tidskriftsartikel (refereegranskat)abstract Optical observations of the aurora have traditionally focused on the structure, intensity, and wavelength of the emissions. But the apparent motion of auroral forms offers another important diagnostic tool for investigating this poorly understood phenomenon. Prior analyses of auroral motion have focused on tracing individual features. In this letter, we investigate the feasibility of deriving the entire two-dimensional velocity field automatically using robust optical flow estimation. The analysis is applied to two narrow-field video sequences. Both examples are rich in small-scale structure and motion, but appear very different to the eye. The robust optical flow estimator performed well for regions of dense turbulent motion, while sheared flow and flow which is perpendicular to image intensity gradients, was poorly resolved. The relative magnitude of the outliers provides a quantitative measure of the validity of the underlying flow model and, hence, a means of automatically differentiating among auroral forms with differing physical origins. The technique can be used to deduce ionospheric electric fields and neutral winds, and the flow fields yield important physical information about the generation mechanism.
7.	Blomberg, Erik, 1987, et al. (författare) Forest Biomass Retrieval from L-Band SAR Using Tomographic Ground Backscatter Removal 2018 Ingår i: IEEE Geoscience and Remote Sensing Letters. - 1558-0571 .- 1545-598X. ; 15:7, s. 1030-1034 Tidskriftsartikel (refereegranskat)abstract A tomographic synthetic aperture radar (TomoSAR) represents a possible route to improved retrievals of forest parameters. Simulated orbital L-band TomoSAR data corresponding to the proposed Satellites for Observation and Communications-Companion Satellite (SAOCOM-CS) mission (1.275 GHz) are evaluated for retrieval of above-ground biomass in boreal forest. L-band data and biomass measurements, collected at the Krycklan test site in northern Sweden as part of the BioSAR 2008 campaign, are used to compare biomass retrievals from SAOCOM-CS to those based on SAOCOM SAR data. Both data sets are in turn compared with the corresponding airborne case, as represented by experimental airborne SAR through processing of the original SAR data. TomoSAR retrievals use a model involving a logarithmic transform of the volumetric backscatter intensity, Ivol, defined as the total backscatter originating between 10 and 30 m above ground. SAR retrievals are obtained with slope-compensated intensity γ0using the same model. It is concluded that tomography using SAOCOM-CS represents an improvement over an airborne SAR imagery, resulting in biomass retrievals from a single polarization (HH) having a 26%-30% root-mean-square error with a little to no impact from the look direction or the local topography.
8.	Campos, Alexandre Becker, 1997-, et al. (författare) False Alarm Reduction in Wavelength-Resolution SAR Change Detection Schemes by Using a Convolutional Neural Network 2022 Ingår i: IEEE Geoscience and Remote Sensing Letters. - : Institute of Electrical and Electronics Engineers Inc.. - 1545-598X .- 1558-0571. ; 19 Tidskriftsartikel (refereegranskat)abstract In this letter, we propose a method to reduce the number of false alarms in a wavelength-resolution synthetic aperture radar (SAR) change detection scheme by using a convolutional neural network (CNN). The detection is performed in two steps: change analysis and object classification. A simple technique for wavelength-resolution SAR change detection is implemented to extract potential targets from the image of interest. A CNN is then used for classifying the change map detections as either a target or nontarget, further reducing the false alarm rate (FAR). The scheme is tested for the CARABAS-II data set, where only three false alarms over a testing area of 96 km² are reported while still sustaining a probability of detection above 96%. We also show that the network can still reduce the FAR even when the flight heading of the SAR system measurement campaign differs by up to 100° between the images used for training and test. CCBY
9.	Diaw, Moustapha, et al. (författare) Optical Aerial Images Change Detection Based on a Color Local Dissimilarity Map and k-Means Clustering 2022 Ingår i: IEEE Geoscience and Remote Sensing Letters. - : IEEE. - 1545-598X .- 1558-0571. ; 19 Tidskriftsartikel (refereegranskat)abstract Considering the unavailability of labeled data sets in remote sensing change detection, this letter presents a novel and low complexity unsupervised change detection method based on the combination of similarity and dissimilarity measures: mutual information (MI), disjoint information (DI), and local dissimilarity map (LDM). MI and DI are calculated on sliding windows with a step of 1 pixel for each pair of channels of both images. The resulting scalar values, weighted by q and m coefficients, are multiplied by the values of the center pixels of the windows weighted by p to remove the textures on images. The changes are detected using, respectively, the grayscale LDM and color LDM. A sliding window is then used on the color LDM and each pixel is characterized by a two-parameter Weibull distribution. Binarized change maps can be obtained by using a k-means clustering on the model parameters. Experiments on optical aerial image data set show that the proposed method produces comparable, even better results, to the state-of-the-art methods in terms of recall, precision, and F-measure.
10.	Gomes, Natanael Rodrigues, et al. (författare) Comparison of the Rayleigh and K-Distributions for Application in Incoherent Change Detection 2019 Ingår i: IEEE Geoscience and Remote Sensing Letters. - : IEEE. - 1545-598X .- 1558-0571. ; 16, s. 756-760 Tidskriftsartikel (refereegranskat)abstract 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.
11.	Hafner, Sebastian, et al. (författare) Sentinel-1 and Sentinel-2 Data Fusion for Urban Change Detection Using a Dual Stream U-Net 2022 Ingår i: IEEE Geoscience and Remote Sensing Letters. - : Institute of Electrical and Electronics Engineers (IEEE). - 1545-598X .- 1558-0571. ; 19 Tidskriftsartikel (refereegranskat)abstract Urbanization is progressing rapidly around the world. With sub-weekly revisits at global scale, Sentinel-1 synthetic aperture radar (SAR) and Sentinel-2 multispectral imager (MSI) data can play an important role for monitoring urban sprawl to support sustainable development. In this letter, we proposed an urban change detection (CD) approach featuring a new network architecture for the fusion of SAR and optical data. Specifically, a dual stream concept was introduced to process different data modalities separately, before combining extracted features at a later decision stage. The individual streams are based on U-Net architecture that is one of the most popular fully convolutional networks used for semantic segmentation. The effectiveness of the proposed approach was demonstrated using the Onera Satellite CD (OSCD) dataset. The proposed strategy outperformed other U-Net-based approaches in combination with unimodal data and multimodal data with feature level fusion. Furthermore, our approach achieved state-of-the-art performance on the urban CD problem posed by the OSCD dataset. Our Sentinel-1 SAR data and code are available on https://github.com/SebastianHafner/DS_UNet.
12.	Jiang, Linfeng, et al. (författare) DSFPAP-Net : Deeper and Stronger Feature Path Aggregation Pyramid Network for Object Detection in Remote Sensing Images 2024 Ingår i: IEEE Geoscience and Remote Sensing Letters. - : Institute of Electrical and Electronics Engineers (IEEE). - 1545-598X .- 1558-0571. ; 21 Tidskriftsartikel (refereegranskat)abstract Rapid detection of small objects in remote sensing (RS) images is crucial for intelligence acquisition, for instance, enemy ship detection. Instead of employing images with high resolution, low-resolution images of the same size typically cover a wider area and thus facilitate efficient object detection. However, accurately detecting small objects in such images remains a challenge due to their limited visual information and the difficulty in distinguishing them from the background. To address this issue, we propose a small object detection method called the deeper and stronger feature path aggregation pyramid network (DSFPAP-Net) for low-resolution RS images. First, our approach involves designing aggregation networks with deeper paths and utilizing feature layers closer to the shallow layers to enhance the acquisition of information about small objects. Second, to enhance the network's focus on small objects, we propose a resolution-adjustable 3-D weighted attention (RA3-DWA) mechanism. This mechanism enables independent learning of spatial feature information and assigns 3-D weights specifically to small objects, resulting in improved detection accuracy for small objects. Finally, we propose the Fast-EIoU loss function to accelerate the regression of the model boundary. This loss function assigns an acceleration factor to the length loss and width loss, respectively, thereby improving the detection accuracy of small objects. Experiments on Levir-Ship and DOTA demonstrate the effectiveness and efficiency of the proposed method. Compared to the baseline YOLOv5, our method has improved the average detection accuracy of the Levir-Ship dataset by 6.7% (reaching up to 82.6%) and the accuracy of the DOTA dataset by 6.4% (reaching up to 73.7%).
13.	John, Viju Oommen, et al. (författare) A cautionary note on the use of Gaussian statistics in satellite-based UTH climatologies 2006 Ingår i: IEEE Geoscience and Remote Sensing Letters. - 1545-598X .- 1558-0571. ; 3:1, s. 130-134 Tidskriftsartikel (refereegranskat)abstract This letter presents a cautionary note on the assumption of Gaussian behavior for upper tropospheric humidity (UTH) derived from satellite data in climatological studies, which can introduce a wet bias in the climatology. An example study using European Centre for Medium-Range Weather Forecasts reanalysis data shows that this wet bias can reach up to 6 %RH, which is significant for climatological applications. A simple Monte Carlo approach demonstrates that these differences and their link to the variability of brightness temperatures are due to a log-normal distribution of the UTH. This problem can be solved by using robust estimators such as the median instead of the arithmetic mean.
14.	Karabacak, Cesur, et al. (författare) Knowledge Exploitation for Human Micro-Doppler Classification 2015 Ingår i: IEEE Geoscience and Remote Sensing Letters. - : IEEE Press. - 1545-598X .- 1558-0571. ; 12:10, s. 2125-2129 Tidskriftsartikel (refereegranskat)abstract Micro-Doppler radar signatures have great potential for classifying pedestrians and animals, as well as their motion pattern, in a variety of surveillance applications. Due to the many degrees of freedom involved, real data need to be complemented with accurate simulated radar data to be able to successfully design and test radar signal processing algorithms. In many cases, the ability to collect real data is limited by monetary and practical considerations, whereas in a simulated environment, any desired scenario may be generated. Motion capture (MOCAP) has been used in several works to simulate the human micro-Doppler signature measured by radar; however, validation of the approach has only been done based on visual comparisons of micro-Doppler signatures. This work validates and, more importantly, extends the exploitation of MOCAP data not just to simulate micro-Doppler signatures but also to use the simulated signatures as a source of a priori knowledge to improve the classification performance of real radar data, particularly in the case when the total amount of data is small.
15.	Kusetogullari, Hüseyin, 1981-, et al. (författare) Change Detection in Multispectral Landsat Images Using Multiobjective Evolutionary Algorithm 2017 Ingår i: IEEE Geoscience and Remote Sensing Letters. - : IEEE. - 1545-598X .- 1558-0571. ; 14:3, s. 414-418 Tidskriftsartikel (refereegranskat)abstract 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.
16.	Ludwig Barbosa, Vinícius, 1990-, et al. (författare) GNSS Radio Occultation Simulation Using Multiple Phase Screen Orbit Sampling 2020 Ingår i: IEEE Geoscience and Remote Sensing Letters. - : Institute of Electrical and Electronics Engineers (IEEE). - 1545-598X .- 1558-0571. ; 17:8, s. 1323-1327 Tidskriftsartikel (refereegranskat)abstract 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.
17.	Martinsson, Jesper, et al. (författare) A New Model for the Distribution of Observable Earthquake Magnitudes and Applications to b-Value Estimation 2018 Ingår i: IEEE Geoscience and Remote Sensing Letters. - : IEEE. - 1545-598X .- 1558-0571. ; 15:6, s. 833-837 Tidskriftsartikel (refereegranskat)abstract The b-value in the Gutenberg–Richter (GR) law contains information that is essential for evaluating earthquake hazard and predicting the occurrence of large earthquakes. Estimates of b are often based on seismic events whose magnitude exceed a certain threshold, the so-called magnitude of completeness. Such estimates are sensitive to the choice of threshold and often ignore a substantial portion of available data. We present a general model for the distribution of observable earthquake magnitudes and an estimation procedure that takes all measurements into account. The model is obtained by generalizing previous probabilistic descriptions of sensor network limitations and using a generalization of the GR law. We show that our model is flexible enough to handle spatio-temporal variations in the seismic environment and captures valuable information about sensor network coverage. We also show that the model leads to significantly improved b-value estimates compared with established methods relying on the magnitude of completeness.
18.	Najim, Safa A., et al. (författare) FSPE: Visualisation of Hyperspectral Imagery Using Faithful Stochastic Proximity Embedding 2015 Ingår i: IEEE Geoscience and Remote Sensing Letters. - 1545-598X .- 1558-0571. ; 12:1, s. 18-22 Tidskriftsartikel (refereegranskat)abstract Hyperspectral image visualization reduces color bands to three, but prevailing linear methods fail to address data characteristics, and nonlinear embeddings are computationally demanding. Qualitative evaluation of an embedding is also lacking. We propose Faithful Stochastic Proximity Embedding (FSPE), a scalable, nonlinear dimensionality reduction method. FSPE considers the nonlinear characteristics of spectral signatures, yet it avoids the costly computation of geodesic distances that are often required by other nonlinear methods. Furthermore, we introduce a point-wise metric that measures the quality of hyperspectral image visualization at each pixel. FSPE outperforms the state-of-art methods by at least 12% on average, and up to 25% in the proposed qualitative measure. An implementation on Graphics Processing Units (GPUs) is two magnitudes faster than the baseline. Our method opens the path to high-fidelity, real-time analysis of hyperspectral images.
19.	Niu, Xin, 1983-, et al. (författare) A Novel Contextual Classification Algorithm for Multitemporal Polarimetric SAR Data 2014 Ingår i: IEEE Geoscience and Remote Sensing Letters. - 1545-598X .- 1558-0571. ; 11:3, s. 681-685 Tidskriftsartikel (refereegranskat)abstract This letter presents a pixel-based contextual classification algorithm by integrating a multiscale modified Pappas adaptive clustering (mMPAC) and an adaptive Markov random field (AMRF) into the stochastic expectation-maximization process for urban land cover mapping using multitemporal polarimetric synthetic aperture radar (PolSAR) data. This algorithm can effectively explore spatiotemporal contextual information to improve classification accuracy. Using the mMPAC, the problem caused by the class feature variation could be mitigated. Using the AMRF, shape details could be preserved from overaveraging that often occurs in many nonadaptive contextual approaches. Six-date RADARSAT-2 PolSAR data over the Greater Toronto Area were used for evaluation. The results show that this algorithm outperformed the support vector machine in producing homogeneous and detailed land cover classification in a complex urban environment with high accuracy.
20.	Palm, Bruna, et al. (författare) Rayleigh Regression Model for Ground Type Detection in SAR Imagery 2019 Ingår i: IEEE Geoscience and Remote Sensing Letters. - : IEEE. - 1545-598X .- 1558-0571. ; 16:10, s. 1660-1664 Tidskriftsartikel (refereegranskat)abstract 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.
21.	Qin, Yuchu, et al. (författare) Toward an Optimal Algorithm for LiDAR Waveform Decomposition 2012 Ingår i: IEEE Geoscience and Remote Sensing Letters. - 1545-598X .- 1558-0571. ; 9:3, s. 482-486 Tidskriftsartikel (refereegranskat)abstract This letter introduces a new approach for light detection and ranging (LiDAR) waveform decomposition. First, inflection points are identified by the Ramer-Douglas-Peucker curve-fitting algorithm, and each inflection point has a corresponding baseline during curve fitting. Second, according to the spatial relation between the baseline and the inflection point, peaks are selected from the inflection points. The distance between each peak and its baseline and the maximum number of peaks are employed as a criterion to select a "significant" peak. Initial parameters such as width and boundaries of peaks provide restraints for the decomposition; right and left boundaries are estimated via a conditional search. Each peak is fitted by a Gaussian function separately, and other parts of the waveform are fitted as line segments. Experiments are implemented on waveforms acquired by both small-footprint LiDAR system LMS-Q560 and large-footprint LiDAR system Laser Vegetation Imaging Sensor. The results indicate that the algorithm could provide an optimal solution for LiDAR waveform decomposition.
22.	Renato, Machado, et al. (författare) The stability of UWB low-frequency SAR images 2016 Ingår i: IEEE Geoscience and Remote Sensing Letters. - : IEEE. - 1545-598X .- 1558-0571. ; 13:8, s. 1114-1118 Tidskriftsartikel (refereegranskat)abstract 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.
23.	Sandberg, Gustaf, 1982, et al. (författare) Measurements of Faraday Rotation Using Polarimetric PALSAR Images 2009 Ingår i: IEEE Geoscience and Remote Sensing Letters. - 1558-0571 .- 1545-598X. ; 6:1, s. 142-146 Tidskriftsartikel (refereegranskat)abstract For spaceborne synthetic aperture radar (SAR) systemsoperating at L-band frequencies or lower, the ionospheremay have a significant impact on the SAR images. The largesteffect at L-band is caused by Faraday rotation (FR). Severalstudies have modeled the effect of FR and/or devised models to measure and correct FR.With the launch of the fully polarimetric L-band system Phased Array-type L-band SAR (PALSAR), it has become possible to test both models and measurement techniques on real SAR data. In this letter, the quality of calibrated polarimetric PALSAR data is assessed, and FR is measured. It is found that residual crosstalk and channel imbalance are small in the PALSAR data. Two methods are used to measure FR, the first using in-scene distributed targets and the second using large trihedrals. The two methods show very good agreement. The measurements are compared with values of the total electron content using a linear model. It is found that the model and measurements are in good agreement, with a root-mean-square error of 0.3◦ or 15% of the mean FR angle.
24.	Soja, Maciej, 1985, et al. (författare) Estimation of Boreal Forest Properties From TanDEM-X Data Using Inversion of the Interferometric Water Cloud Model 2017 Ingår i: IEEE Geoscience and Remote Sensing Letters. - 1558-0571 .- 1545-598X. ; 14:7, s. 997-1001 Tidskriftsartikel (refereegranskat)abstract In this letter, the interferometric water cloud model (IWCM) is fit to 87 VV-polarized TanDEM-X acquisitions made between June 2011 and August 2014 over a boreal forest in Krycklan, northern Sweden, using a new method based on nonlinear least-squares optimization. A high-resolution digital terrain model is used as ground reference during interferometric synthetic-aperture radar (InSAR) processing and 26 stands with areas 1.5-22 ha and unaltered during the study period are studied. The dependence of biomass estimation performance, ground and vegetation backscatter coefficients (sigma(0)(gr) and sigma(0)(veg)), canopy attenuation (alpha), and zero-biomass coherence (gamma 0) on selected system and environmental parameters is studied. High correlation between the estimated biomass and reference biomass derived from in situ measurements is observed for all 87 acquisitions (r between 0.81 and 0.93), while the root-mean-square difference is between 18% and 32% for all 43 acquisitions made in snow-free conditions and with heights-of-ambiguity (HOAs) between 36 and 150 m. Significant biomass estimation bias is observed for HOAs above 150 m and for some acquisitions over snow-covered forest. It is also observed that sigma(0)(gr) and sigma(0)(veg) are the largest for temperatures below 0 degrees C and with significant snow cover. For temperatures above 0 degrees C, sigma(0)(gr) appears independent of temperature, while sigma(0)(veg) shows a tendency to increase with temperature. Moreover, gamma 0 decreases from just below 1 for HOAs around 40 m to around 0.8 for HOAs above 150 m.
25.	Soja, Maciej, 1985, et al. (författare) Estimation of Forest Height and Canopy Density From a Single InSAR Correlation Coefficient 2015 Ingår i: IEEE Geoscience and Remote Sensing Letters. - : Institute of Electrical and Electronics Engineers (IEEE). - 1558-0571 .- 1545-598X. ; 12:3, s. 646-650 Tidskriftsartikel (refereegranskat)abstract A two-level model (TLM) is introduced and investigated for the estimation of forest height and canopy density from a single ground-corrected InSAR complex correlation coefficient. The TLM models forest as two scattering levels, namely, ground and vegetation, separated by a distance Delta h and with area-weighted backscatter ratio mu. The model is evaluated using eight VV-polarized bistatic-interferometric TanDEM-X image pairs acquired in the summers of 2011, 2012, and 2013 over the managed hemi-boreal test site Remningstorp, which is situated in southern Sweden. Ground phase is removed using a high-resolution digital terrain model. Inverted TLM parameters for thirty-two 0.5-ha plots of four different types (regular plots, sparse plots, seed trees, and clear-cuts) are studied against reference lidar data. It is concluded that the level distance Delta h can be used as an estimate of the 50th percentile forest height estimated from lidar (for regular plots: r > 0.95 and root-mean-square difference (sigma) 0.59 and sigma approximate to 10%, or 0.07).
26.	Strandberg, Joakim, 1991, et al. (författare) Can We Measure Sea Level With a Tablet Computer? 2020 Ingår i: IEEE Geoscience and Remote Sensing Letters. - 1558-0571 .- 1545-598X. ; 17:11, s. 1876-1878 Tidskriftsartikel (refereegranskat)abstract Modern mobile phones and tablet computers can have the capacity to store raw Global Navigation Satellite System (GNSS) data for further processing. With a short proof-of-concept campaign, we show that such data, recorded with a tablet computer, can be used to measure the sea level using GNSS reflectometry (GNSS-R). The results suggest that the tablet computer performs on a similar level as more high-end, geodetic-quality equipment.
27.	Strandberg, Joakim, 1991, et al. (författare) Coastal Sea Ice Detection Using Ground-Based GNSS-R 2017 Ingår i: IEEE Geoscience and Remote Sensing Letters. - 1558-0571 .- 1545-598X. ; 14:9, s. 1552-1556 Tidskriftsartikel (refereegranskat)abstract Determination of sea ice extent is important both for climate modeling and transportation planning. Detection and monitoring of ice are often done by synthetic aperture radar imagery, but mostly without any ground truth. For the latter purpose, robust and continuously operating sensors are required. We demonstrate that signals recorded by ground-based Global Navigation Satellite System (GNSS) receivers can detect coastal ice coverage on nearby water surfaces. Beside a description of the retrieval approach, we discuss why GNSS reflectometry is sensitive to the presence of sea ice. It is shown that during winter seasons with freezing periods, the GNSS-R analysis of data recorded with a coastal GNSS installation clearly shows the occurrence of ice in the bay where this installation is located. Thus, coastal GNSS installations could be promising sources of ground truth for sea ice extent measurements.
28.	Tang, Shuhang, et al. (författare) Reconstruction of Sparsely Sampled Seismic Data via Residual U-Net 2022 Ingår i: IEEE Geoscience and Remote Sensing Letters. - : Institute of Electrical and Electronics Engineers (IEEE). - 1545-598X .- 1558-0571. ; 19 Tidskriftsartikel (refereegranskat)abstract Reconstruction of sparsely sampled seismic data is critical for maintaining the quality of seismic images when significant numbers of shots and receivers are missing. We present a reconstruction method in the shot-receiver-time (SRT) domain based on a residual U-Net machine learning architecture, for seismic data acquired in a sparse 2-D acquisition and name it SRT2D-ResU-Net. The SRT domain retains a high level of seismic signal connectivity, which is likely the main data feature that the reconstructing algorithms rely on. We develop an "in situ training and prediction" workflow by dividing the acquisition area into two nonoverlapping subareas: a training subarea for establishing the network model using regularly sampled data and a testing subarea for reconstructing the sparsely sampled data using the trained model. To establish a reference base for analyzing the changes in data features over the study area, and quantifying the reconstructed seismic data, we devise a baseline reference using a tiny portion of the field data. The baselines are properly spaced and excluded from the training and reconstruction processes. The results on a field marine data set show that the SRT2D-ResU-Net can effectively learn the features of seismic data in the training process, and the average correlation between the reconstructed missing traces and the true answers is over 85%.
29.	Ulander, Lars, 1962, et al. (författare) Multiport vector network analyzer radar for tomographic forest scattering measurements 2018 Ingår i: IEEE Geoscience and Remote Sensing Letters. - 1558-0571 .- 1545-598X. ; 15:12, s. 1897-1901 Tidskriftsartikel (refereegranskat)abstract We describe a P-, L- A nd C-band radar, BorealScat, designed for polarimetric time-series measurements of forests. Radar tomography is implemented with a vertical antenna array, which provides measurements of the vertical scattering distribution. To minimize temporal decorrelation, the radar performs simultaneous measurements of the reflected signals using all array elements. The system is implemented using a 20-port vector network analyzer (VNA) and a stepped-frequency waveform. It has two 20-element arrays: One array optimized for P- A nd L-bands and one for C-band. The arrays are installed on a 50-m high tower and radar measurements are collected over a hemiboreal forest stand. We discuss several design issues and demonstrate some tomographic imaging capabilities. The multiport VNA tomography results are compared with results from the system operating in the slower 2-port VNA measurement scheme.
30.	Viet Thuy, Vu (författare) Wavelength-resolution SAR Incoherent ChangeDetection Based on Image Stack 2017 Ingår i: IEEE Geoscience and Remote Sensing Letters. - : IEEE. - 1545-598X .- 1558-0571. ; 14:7, s. 1012-1016 Tidskriftsartikel (refereegranskat)abstract 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.
31.	Vinholi, João Gabriel, et al. (författare) CNN-Based Change Detection Algorithm for Wavelength-Resolution SAR Images 2022 Ingår i: IEEE Geoscience and Remote Sensing Letters. - : Institute of Electrical and Electronics Engineers (IEEE). - 1545-598X .- 1558-0571. ; 19 Tidskriftsartikel (refereegranskat)abstract This letter presents an incoherent change detectionalgorithm (CDA) for wavelength-resolution synthetic apertureradar (SAR) based on convolutional neural networks (CNNs).The proposed CDA includes a segmentation CNN, whichlocalizes potential changes, and a classification CNN, whichfurther analyzes these candidates to classify them as real changesor false alarms. Compared to state-of-the-art solutions on theCARABAS-II data set, the proposed CDA shows a significantimprovement in performance, achieving, in a particular setting,a detection probability of 99% at a false alarm rate of0.0833/km2
32.	Vu, Viet Thuy, et al. (författare) Derivation of Bistatic SAR Resolution Equations Based on Backprojection 2018 Ingår i: IEEE Geoscience and Remote Sensing Letters. - : Institute of Electrical and Electronics Engineers Inc.. - 1545-598X .- 1558-0571. ; 15:5, s. 694-698 Tidskriftsartikel (refereegranskat)abstract 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
33.	Vu, Viet Thuy, et al. (författare) RFI Suppression in Ultrawideband SAR Using an Adaptive Line Enhancer 2010 Ingår i: IEEE Geoscience and Remote Sensing Letters. - : IEEE. - 1545-598X .- 1558-0571. ; 7:4, s. 694-698 Tidskriftsartikel (refereegranskat)abstract 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.
34.	Vu, Viet Thuy, 1977-, et al. (författare) Sidelobe Control for Bistatic SAR Imaging 2022 Ingår i: IEEE Geoscience and Remote Sensing Letters. - : Institute of Electrical and Electronics Engineers Inc.. - 1545-598X .- 1558-0571. ; 19 Tidskriftsartikel (refereegranskat)abstract This letter presents coherent and incoherent nonlinear apodization methods for bistatic synthetic aperture radar (SAR) imaging. The methods are developed on the principle of nonlinear apodization for monostatic SAR imaging and a ω - k relationship representing the bistatic region of support. This relationship plays an important role in designing 2-D windows for the apodization methods. The simulation results show that the presented apodization methods work efficiently with bistatic SAR imaging. In the experiment with a coherent dual apodization (CDA) method presented in this letter, the sidelobe attenuates very fast, and the peak sidelobe is reduced about 16 dB, while the resolutions in azimuth and range are maintained. CCBY
35.	Vu, Viet Thuy, 1977-, et al. (författare) Tilt phenomenon in bistatic SAR image 2022 Ingår i: IEEE Geoscience and Remote Sensing Letters. - : Institute of Electrical and Electronics Engineers Inc.. - 1545-598X .- 1558-0571. ; 19 Tidskriftsartikel (refereegranskat)abstract The tilt phenomenon or skew in bistatic SAR images has been known. This can be observed from the SAR image of a point-like scatterer, even with a symmetrical bistatic aperture. This letter explains this phenomenon in bistatic SAR images and shows that the phenomenon depends on the initial and the last positions of the transmitter and receiver platforms. A formula to calculate the tilt angle based on a general bistatic geometry is provided. This formula supports bistatic SAR system design and bistatic image quality measurements. Author
36.	Vu, Viet Thuy, et al. (författare) Ultrawideband Chirp Scaling Algorithm 2010 Ingår i: IEEE Geoscience and Remote Sensing Letters. - : IEEE. - 1545-598X .- 1558-0571. ; 7:2, s. 281-185 Tidskriftsartikel (refereegranskat)abstract 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.
37.	Vu, Viet, et al. (författare) Two-Dimensional Spectrum for BiSAR Derivation Based on Lagrange Inversion Theorem 2014 Ingår i: IEEE Geoscience and Remote Sensing Letters. - : IEEE. - 1545-598X .- 1558-0571. ; 11:7, s. 1210-1214 Tidskriftsartikel (refereegranskat)abstract 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.
38.	Wang, Wei, et al. (författare) Integrating Contextual Information With H/(alpha)over-bar Decomposition for PolSAR Data Classification 2016 Ingår i: IEEE Geoscience and Remote Sensing Letters. - : IEEE. - 1545-598X .- 1558-0571. ; 13:12, s. 2034-2038 Tidskriftsartikel (refereegranskat)abstract The use of contextual information is beneficial to improve both the accuracy and reliability of image classification. Based on the robust fuzzy c-means (RFCM) clustering method and an adaptive Markov random field model, this letter proposes a contextual H/(alpha) over bar classifier for polarimetric synthetic aperture radar images. At each iterative step of RFCM clustering, the prior probability extracted from the local neighborhood is combined with the fuzzy membership derived from inherent polarimetric characteristics, thus the enhanced fuzzy membership is more reliable. In addition, an adaptive smoothing factor is proposed for use during contextual information retrieval, which can prevent oversmoothing and preserve the local spatial details. The experimental results implemented using AIRSAR and ESAR L-band data validate the efficacy of the proposed method. Compared with the iterated Wishart classifier and fuzzy H/(alpha) over bar classifier, the proposed method significantly improves the classification accuracy, with less noise and increased preservation of details.
39.	Xiang, Deliang, et al. (författare) Edge Detector for Polarimetric SAR Images Using SIRV Model and Gauss-Shaped Filter 2016 Ingår i: IEEE Geoscience and Remote Sensing Letters. - : Institute of Electrical and Electronics Engineers (IEEE). - 1545-598X .- 1558-0571. ; 13:11, s. 1661-1665 Tidskriftsartikel (refereegranskat)abstract The classic constant false alarm rate edge detector with a rectangle-shaped filter has been proven to be effective and widely used in polarimetric synthetic aperture radar (PolSAR) images. However, in practical use, the assumption of complex Wishart distribution is often not respected, particularly in heterogeneous urban areas. In addition, as a simple smoothing filter, the rectangle-shaped window is often shown to be easy to incur false edge pixels near true edges. Therefore, its performance is limited. To overcome this restriction, we propose a new edge detector for PolSAR images, which utilizes the spherically invariant random vector product model to estimate the normalized covariance matrix for each pixel, and then replace the rectangle-shaped filter with a Gauss-shaped filter. The performance of our proposed methodology is presented and analyzed on two real PolSAR data sets, and the results show that the new edge detector attains better performance than the classic one, particularly for urban areas.
40.	Xiang, Deliang (författare) Edge Detector for Polarimetric SAR ImagesUsing SIRV Model and Gauss-Shaped Filter 2024 Ingår i: IEEE Geoscience and Remote Sensing Letters. - : IEEE Press. - 1545-598X .- 1558-0571. Tidskriftsartikel (refereegranskat)abstract The classic constant false alarm rate (CFAR) edgedetector with rectangle-shaped filter has been proven to beeffective and widely used in polarimetric SAR (PolSAR) images.However, in practical use, the assumption of complex Wishartdistribution is often not respected, especially in heterogeneousurban areas. In addition, as a simple smoothing filter, therectangle-shaped window is often shown to be easy to incur falseedge pixels near true edges. Therefore, its performance islimited. To overcome this restriction, we propose a new edgedetector for PolSAR images, which utilizes the sphericallyinvariant random vector (SIRV) product model to estimate thenormalized covariance matrix for each pixel and then replacethe rectangle-shaped filter with Gauss-shaped filter. Theperformance of our proposed methodology is presented andanalyzed on two real PolSAR data sets, and the results show thatthe new edge detector attains better performance than theclassic one, particularly for urban areas.
41.	Xiang, Deliang, 1989-, et al. (författare) Model-Based Decomposition With Cross Scattering for Polarimetric SAR Urban Areas 2015 Ingår i: IEEE Geoscience and Remote Sensing Letters. - : IEEE Press. - 1545-598X .- 1558-0571. ; 12:12, s. 2496-2500 Tidskriftsartikel (refereegranskat)abstract Cross-polarized scattering (HV) is not only caused by vegetation but also by rotated dihedrals. In this letter, we use rotated dihedral corner reflectors to form a cross scattering matrix and propose an extended model-based decomposition method for polarimetric synthetic aperture radar (PolSAR) data over urban areas. Unlike other urban decomposition techniques which need to discriminate between urban and natural areas before decomposition, this proposed method is applied directly on the PolSAR image. The building orientation angle is considered in this scattering matrix, making it flexible and adaptive in the decomposition process. This enables the separation of the cross scattering of urban areas from the overall HV component. The cross and helix scattering components are also compared in this study. RADARSAT-2 quad-pol C band and AIRSAR L band data are used to validate the performance of the proposed method. The cross scattering power of oriented buildings is generated, leading to a better decomposition result for urban areas with respect to other urban decomposition techniques.
42.	Butt, Naveed, et al. (författare) Classification of Raman Spectra to Detect Hidden Explosives 2011 Ingår i: IEEE Geoscience and Remote Sensing Letters. - : IEEE. - 1545-598X. ; 8:3, s. 517-521 Tidskriftsartikel (refereegranskat)abstract Raman spectroscopy is a laser-based vibrational technique that can provide spectral signatures unique to a multitude of compounds. The technique is gaining widespread interest as a method for detecting hidden explosives due to its sensitivity and ease of use. In this letter, we present a computationally efficient classification scheme for accurate standoff identification of several common explosives using visible-range Raman spectroscopy. Using real measurements, we evaluate and modify a recent correlation-based approach to classify Raman spectra from various harmful and commonplace substances. The results show that the proposed approach can, at a distance of 30 m, or more, successfully classify measured Raman spectra from several explosive substances, including nitromethane, trinitrotoluene, dinitrotoluene, hydrogen peroxide, triacetone triperoxide, and ammonium nitrate.
43.	Feng, Wenqing, et al. (författare) Water Body Extraction From Very High-Resolution Remote Sensing Imagery Using Deep U-Net and a Superpixel-Based Conditional Random Field Model 2019 Ingår i: IEEE Geoscience and Remote Sensing Letters. - 1545-598X. ; 16:4, s. 618-622 Tidskriftsartikel (refereegranskat)abstract Water body extraction (WBE) has attracted considerable attention in the field of remote sensing image analysis. Herein, we present an enhanced deep convolutional encoder-decoder (DCED) network (or Deep U-Net) specifically tailored to WBE from remote sensing images by applying superpixel segmentation and conditional random fields (CRFs). First, we preclassify the entire remote sensing image into the water and nonwater areas via Deep U-Net, using the results of class membership probabilities as the unary potential in the CRF model. The pairwise potential of CRF is defined by a linear combination of Gaussian kernels, which forms a fully connected neighbor structure. Next, regional restriction is incorporated into the approach to enhance the consistency of the connected area. We use the simple linear iterative clustering algorithm to generate superpixels and correct the binary classification results by calculating their average posterior probabilities. Finally, a highly efficient approximate inference algorithm, mean-field inference, is generated for the final model. The results from the experimental application to GaoFen-2 images and WorldView-2 images demonstrate that the proposed approach exhibits competitive quantitative and qualitative performance, which effectively reduces salt-and-pepper noise and retains the edge structures of water bodies. Compared to existing state-of-the-art methods, our proposed method achieves superior final results.
44.	Persson, Henrik (författare) Estimation of Forest Height and Canopy Density From a Single InSAR Correlation Coefficient 2015 Ingår i: IEEE Geoscience and Remote Sensing Letters. - 1545-598X. ; 12, s. 646-650 Tidskriftsartikel (refereegranskat)abstract A two-level model (TLM) is introduced and investigated for the estimation of forest height and canopy density from a single ground-corrected InSAR complex correlation coefficient. The TLM models forest as two scattering levels, namely, ground and vegetation, separated by a distance Delta h and with area-weighted backscatter ratio mu. The model is evaluated using eight VV-polarized bistatic-interferometric TanDEM-X image pairs acquired in the summers of 2011, 2012, and 2013 over the managed hemi-boreal test site Remningstorp, which is situated in southern Sweden. Ground phase is removed using a high-resolution digital terrain model. Inverted TLM parameters for thirty-two 0.5-ha plots of four different types (regular plots, sparse plots, seed trees, and clear-cuts) are studied against reference lidar data. It is concluded that the level distance Delta h can be used as an estimate of the 50th percentile forest height estimated from lidar (for regular plots: r > 0.95 and root-mean-square difference (sigma) < 10%, or 1.8 m). Moreover, the uncorrected area fill factor eta(0) = 1/(1 + mu) can be used as an estimate of the vegetation ratio, which is a canopy density estimate defined as the fraction of lidar returns coming from the canopy to all lidar returns (for regular plots: r > 0.59 and sigma approximate to 10%, or 0.07).
45.	Shi, Tianyue, et al. (författare) Extended PGA for Spotlight SAR-Filtered Backprojection Imagery 2022 Ingår i: IEEE Geoscience and Remote Sensing Letters. - 1545-598X. ; 19 Tidskriftsartikel (refereegranskat)abstract The phase gradient autofocus (PGA) is a robust autofocusing approach that can efficiently refocus defocused synthetic aperture radar (SAR) imagery produced by frequency-domain algorithms. However, from a conventional viewpoint, PGA cannot be extended to refocus SAR imagery produced by time-domain algorithms, such as the filtered backprojection (FBP), as the spectrum of the FBP imagery is range ambiguous and azimuth space-variant. In this letter, a novel interpretation of FBP is presented, in which the spectrum structure of the FBP imagery is analyzed in detail. By incorporating the derived spectral information, an efficient spectrum preprocessing is proposed for spectrum restructuring. After this preprocessing, PGA is shown to be able to refocus defocused FBP imagery. The validity and feasibility of the proposed autofocusing approach are demonstrated using both simulated and experimental data.
46.	Somasundaram, Samuel D., et al. (författare) Countering Radio Frequency Interference in Single Sensor Quadrupole Resonance 2009 Ingår i: IEEE Geoscience and Remote Sensing Letters. - 1545-598X. ; 6:1, s. 62-66 Tidskriftsartikel (refereegranskat)abstract Nuclear quadrupole resonance (NQR) is a solid-state radio frequency (RF) spectroscopic technique that allows for the detection of many narcotics and highly explosive substances. Unfortunately, the practical use of NQR is often restricted by the presence of strong RF interference (RFI). In this letter, extending our recent work on stochastic NQR (sNQR), we propose acquiring signal-of-interest free samples, containing only corrupting signals, and exploiting them to reduce the effects of RFI on conventional NQR (cNQR) measurements. Similar to the sNQR case, the presented detectors are able to substantially outperform previous cNQR detectors when RFI is present.
47.	Zhang, Yongchao, et al. (författare) Online Sparse Reconstruction for Scanning Radar Using Beam-Updating q-SPICE 2022 Ingår i: IEEE Geoscience and Remote Sensing Letters. - 1545-598X. ; 19 Tidskriftsartikel (refereegranskat)abstract The generalized sparse iterative covariance-based estimation ( $q$ -SPICE) algorithm was recently introduced for scanning radar applications, resulting in substantial improvements in the angular resolution and quality of the processed images. Regrettably, the computational complexity and storage cost are high and quickly increase with growing data size, limiting the applicability of the estimator. In this letter, we strive to alleviate this problem, deriving a beam-updating $q$ -SPICE algorithm, allowing for efficiently updating of the sparse reconstruction result for each online radar measurement along the scanned beam. The resulting method is a regularized extension of the current online $q$ -SPICE implementation, which not only offers constant computational and storage cost, independent of the data size, but also provides enhanced robustness over the current online $q$ -SPICE. Our experimental assessment, conducted using both simulated and real data, demonstrates the advantage of the beam-updating $q$ -SPICE method in the task of sparse reconstruction for scanning radar.
48.	Zhang, Yongchao, et al. (författare) Range-Recursive IAA for Scanning RadarAngular Super-Resolution 2017 Ingår i: IEEE Geoscience and Remote Sensing Letters. - 1545-598X. ; 14:10, s. 1675-1679 Tidskriftsartikel (refereegranskat)abstract Recently, the iterative adaptive approach (IAA) was adopted to allow for the estimation of high-resolution scanning radar images. In this letter, we further develop this approach by introducing a range-recursive IAA (IAA-RR) formulation allowing for a computationally efficient updating of the resulting estimates along range. Besides exploiting the rich matrix structure to mitigate the computational complexity for each iteration, the correlation between adjacent range cells is exploited to accelerate the convergence of the IAA iterations. When an additional range measurement becomes available, further acceleration is available by exploiting the estimates already formed for the adjacent range cells. Compared with the existing fast IAA implementation, the proposed IAA-RR is shown to offer significant computational savings, without noticeable loss in performance. Numerical results illustrate the superior performance of the proposed IAA-RR algorithm.

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