| 1. |
- Askne, Jan, 1936, et al.
(författare)
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On the Estimation of Boreal Forest Biomass From TanDEM-X Data Without Training Samples
- 2015
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Ingår i: IEEE Geoscience and Remote Sensing Letters. - : Institute of Electrical and Electronics Engineers (IEEE). - 1558-0571 .- 1545-598X. ; 12:4, s. 771-775
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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.
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| 2. |
- Blomberg, Erik, 1987, et al.
(författare)
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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
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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.
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| 3. |
- Gomes, Natanael Rodrigues, et al.
(författare)
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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.
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| 4. |
- 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
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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.
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| 5. |
- Kusetogullari, Hüseyin, 1981-, et al.
(författare)
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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.
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| 6. |
- 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
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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.
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| 7. |
- Najim, Safa A., et al.
(författare)
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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
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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.
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| 8. |
- Palm, Bruna, et al.
(författare)
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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
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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.
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| 9. |
- Renato, Machado, et al.
(författare)
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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
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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.
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| 10. |
- 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.
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| 11. |
- 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).
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| 12. |
- 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.
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| 13. |
- 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.
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| 14. |
- Viet Thuy, Vu
(författare)
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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.
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| 15. |
- Vu, Viet Thuy, et al.
(författare)
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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
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| 16. |
- Wang, Wei, et al.
(författare)
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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.
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| 17. |
- Xiang, Deliang, et al.
(författare)
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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.
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| 18. |
- 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.
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| 19. |
- 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.
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| 20. |
- 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).
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| 21. |
- Zhang, Yongchao, et al.
(författare)
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Range-Recursive IAA for Scanning RadarAngular Super-Resolution
- 2017
-
Ingår i: IEEE Geoscience and Remote Sensing Letters. - 1545-598X. ; 14:10, s. 1675-1679
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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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