Along-Track Interferometric Synthetic Aperture Radar (ATISAR) has the potential of measuring the radial velocity of the slowly moving target. The accuracy of the radial velocity is mainly determined by the accuracy of...
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ISBN:
(纸本)9781849196031
Along-Track Interferometric Synthetic Aperture Radar (ATISAR) has the potential of measuring the radial velocity of the slowly moving target. The accuracy of the radial velocity is mainly determined by the accuracy of the interferometric parameters. Sensitivity equations are good ways of analysing the impacts of system parameters for interferometric SAR. Former sensitivity analysis for ATI-SAR has been mainly focused on the case of no squint angle. In this paper, we explain the necessity of analysing the sensitivity equations in the presence of squint angle. Then the expression of the radial velocity in the presence of squint is derived and the sensitivity equations are obtained. Finally, the sensitivity of some interferometric parameters and the impact of squint angles are analysed and simulated for a particular accuracy requirement.
Image registration is an important preprocessing step for image processing such as change detection,image mosaicking in remote sensing,however a crucial problem involved feature-based image registration is how to reli...
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Image registration is an important preprocessing step for image processing such as change detection,image mosaicking in remote sensing,however a crucial problem involved feature-based image registration is how to reliably establish correspondent features between sensed image and reference *** paper presents an automatic self-adaptive image registration method based on analytic energy of control points to improve the traditional ***,an multi-scale segment method based on digital curvelet transform is used to evaluate the quality difference of image pairs,and then self-adaptive parameters of SIFT feature-matching algorithm based on multi-scale grey relation of image quality is proposed to increase the feature points and correspondences;At last,to make sure the accuracy of geometrical transform parameters,a method of correspondences selection based on the distribution and matching energy of control points is *** results demonstrate that the proposed method works well in increasing control points and the correspondences of low quality remote sensing images.
Airborne Along-Track Interferometric Synthetic Aperture Radar (ATI-SAR) baseline error is a main error resource affecting the precision of velocity measurement of moving objects and therefore should be calibrated exte...
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Airborne Along-Track Interferometric Synthetic Aperture Radar (ATI-SAR) baseline error is a main error resource affecting the precision of velocity measurement of moving objects and therefore should be calibrated externally. The Jet Propulsion laboratory (JPL) has proposed a calibration scheme for tasks of PacRim98 and PacRim2000 based on several static objects on the ground. In this paper, the influence of phase center uncertainty on baseline determination by using PacRim method proposed by JPL is analyzed. According to the analysis, the phase center uncertainty can cause a constant part of error to the result of baseline calibration. In order to deal with this problem, an improved calibration method on the basis of sensitivity equations and some ground moving targets, whose velocities are already known, is proposed in this paper. The simulation results show that our proposed calibration method has improved the accuracy of baseline calibration and has obviously prohibited the effect of antennas' phase center uncertainty.
geospatial objects detection within complex environment is a challenging problem in remote sensing area. In this paper, we derive an extension of the Relevance Vector Machine (RVM) technique to multiple kernel version...
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geospatial objects detection within complex environment is a challenging problem in remote sensing area. In this paper, we derive an extension of the Relevance Vector Machine (RVM) technique to multiple kernel version. The proposed method learns an optimal kernel combination and the associated classifier simultaneously. Two feature types are extracted from images, forming basis kernels. Then these basis kernels are weighted combined and resulted the composite kernel exploits interesting points and appearance information of objects simultaneously. Weights and the detection model are finally learnt by a new algorithm. Experimental results show that the proposed method improve detection accuracy to above 88%, yields good interpretation for the selected subset of features and appears sparser than traditional single-kernel RVMs.
Road pavement reflectance is usually assumed to be invariant in short periods of time in some quantitative remote sensing *** examine its variability,reflectance sequences of concrete and asphalt pavement are measured...
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Road pavement reflectance is usually assumed to be invariant in short periods of time in some quantitative remote sensing *** examine its variability,reflectance sequences of concrete and asphalt pavement are measured in field for half a day in visible and near-infarecd（VNIR）spectral range using dual-beam *** much as 20.7%and 3.52%of relative changes are found in asphalt and concrete reflectance data at 550 nm,and all VNIR bands demonstrate similar variations found to correlate with both illumination geometry and the relative portion of diffuse *** this letter,this effect is interpreted from a mathematic *** studies are needed to model the dynamics of reflectance physically.
Band-to-band registration accuracy is an important parameter of multispectral data. A novel band-to-band registration approach with high precision is proposed for the multi-spectral images of HJ-1A/B. Firstly, the mai...
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Band-to-band registration accuracy is an important parameter of multispectral data. A novel band-to-band registration approach with high precision is proposed for the multi-spectral images of HJ-1A/B. Firstly, the main causes resulted in misregistration are analyzed, and a high-order polynomial model is proposed. Secondly, a phase fringe filtering technique is employed to Phase Correlation Method based on Singular Value Decomposition (SVD-PCM) for reducing the noise in phase difference matrix. Then, experiments are carried out to build nonlinear registration models, and images of green band and red band are aligned to blue band with an accuracy of 0.1 pixels, while near infrared band with an accuracy of 0.2 pixels.
Range-Doppler (RD) method and Reverse-Range-Doppler (RRD) method are combined together to achieve automatic geocoding of Synthetic Aperture Radar (SAR) image quickly and accurately in the paper. The RD method is first...
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Range-Doppler (RD) method and Reverse-Range-Doppler (RRD) method are combined together to achieve automatic geocoding of Synthetic Aperture Radar (SAR) image quickly and accurately in the paper. The RD method is firstly used to locate the four corners of the image, then the other pixels of the image can be located by Reverse-Range-Doppler (RRD) method. Resampling is performed at last. The approach has an advantage over previous techniques in that it does not require ground control points and is independent of spacecraft attitude knowledge or control. It can compensate the shift due to the assumed Doppler frequency in SAR image preprocessing. RRD simplifies the process of RD, therefore speeds up the computation. The experimental results show that a SAR image can be automated geocoded in 30 s using the single CPU (3 GHz) with 1 G memory and an accuracy of 10 m is attainable with this method.
The layover phenomenon of SAR imaging arises when different height contributions collapse in the same range-azimuth resolution cell, due to the presence of strong terrain slopes or discontinuities in the scenarios. Be...
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ISBN:
(纸本)9781467311601
The layover phenomenon of SAR imaging arises when different height contributions collapse in the same range-azimuth resolution cell, due to the presence of strong terrain slopes or discontinuities in the scenarios. Because of the phase discontinuities, for single baseline interferometric SAR, it is difficult to recover the accurate unwrapped phase in layover areas by traditional phase unwrapping methods. In this paper, according to the phase characteristic of layover areas, we propose a new method to retrieve unwrapped phase based on local frequency estimate. It can avoid the unwrapping error resulted from the phase jump at the edge of layover areas. As a result, relative accurate DEM of layover areas can be reconstructed, which is beneficial to afterward geocoding in InSAR topographic mapping.
Due to the significant azimuth variance property in medium-Earth-orbit (MEO) synthetic aperture radar (SAR) echo, it is difficult for the conventional SAR algorithms to achieve a good compromise between accuracy and e...
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ISBN:
(纸本)9781467311601
Due to the significant azimuth variance property in medium-Earth-orbit (MEO) synthetic aperture radar (SAR) echo, it is difficult for the conventional SAR algorithms to achieve a good compromise between accuracy and efficiency. A novel algorithm based on keystone transform (KT) and azimuth perturbation (AP) is introduced in this paper to handle this problem. The function of KT is to correct the range walk and thus to mitigate the azimuth variance effect on range processing. The function of AP is to equalize the Doppler histories in each range gate and thus to mitigate the azimuth variance effect on azimuth compressing. Simulation results of an L-band MEO SAR with 5 m resolution at 10,000 km altitude demonstrate the capability of our algorithm.
This paper presents a new simplex-based method for unsupervised endmember extraction, called maximum abundance sum-to-one constraint (ASC) fraction (MAF). The ASC fractions refer to the spectral unmixing results with ...
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This paper presents a new simplex-based method for unsupervised endmember extraction, called maximum abundance sum-to-one constraint (ASC) fraction (MAF). The ASC fractions refer to the spectral unmixing results with the abundance sum-to-one constraint unmixing only. The algorithm assumes the existence of the pure pixels in the input data for every endmember in the scene, and exploits the fact that pixels with maximum ASC fractions are corresponding to the vertices of a simplex. In order to demonstrate the performance of the proposed MAF, the N-findr algorithm (N-FINDR) and vertex component analysis (VCA) based merely on PCA dimensional reduction are used for comparison. Experiments using both simulated and real hyperspectral data show that MAF is effective in searching optimal results, with a low computational complexity.
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