Range-Doppler Model Research Articles

A Robust Registration Method for Multi-view SAR Images based on Best Buddy Similarity

Abstract. Due to the influence of imaging angle and terrain undulation, multi-view synthetic aperture radar (SAR) images are difficult to be directly registered by traditional methods. Although feature matching solves the issue of image rotation and maintains scale invariance, these methods often lead to non-uniformity of interest points and may not achieve subpixel accuracy. The traditional template matching method makes it difficult to generate correct matches for multi-view SAR oblique images. In this paper, a multi-view SAR image template matching method based on Best Buddy Similarity (BBS) is proposed to solve the traditional methods' problem. Firstly, the initial correspondences between images are established according to the Range-Doppler model of SAR images. Secondly, a sliding window search is performed on the established correspondence, the BBS is calculated, and the subpixel locations of the peaks on the similarity map are estimated to achieve a fine match. In the calculation process of BBS, the SAR-ROEWA operator is used to suppress the speckle noise of SAR images. The experiment demonstrated that SAR-BBS can accurately match SAR images with large rotation angle. The peak value on the search window is significant. The registration accuracy of SAR-BBS outperforms the other state-of-the-art methods.

First Assessment of Bistatic Geometric Calibration and Geolocation Accuracy of Innovative Spaceborne Synthetic Aperture Radar LuTan-1

LuTan-1 (LT-1) is a bistatic synthetic aperture radar (BiSAR) system consisting of two identical L-band SAR satellites. The bistatic mode of LT-1 plays a critical role in generating high-precision digital elevation models (DEMs), which requires precise geometric calibration of initial range and azimuth times for both SARs to ensure the reliability and quality of geolocation. However, existing geometric calibration methods predominantly focus on monostatic SAR systems, with limited literature on slave SAR calibration in bistatic systems. This research addresses this gap by establishing geometric calibration models for both SARs based on signal echo history and the range–Doppler model. The geometric errors are effectively resolved using corner reflector data from Xinjiang, China. Through statistical analysis of LT-1 SAR images acquired between July and November in bistatic mode, this paper has demonstrated range delay accuracy of better than 5 ns and azimuth time accuracy of better than 0.1 ms. This level of precision translates into a positional accuracy better than 0.8 m. The proposed models have been successfully applied to geometric calibration, providing precise geolocation for LT-1, thus enhancing its utility for a wide range of Earth observation applications. This paper is the first endeavor to present the assessment of the geometric calibration and geolocation accuracy of LT-1 and discuss the results of the bistatic geometric calibration of the master and slave SARs in a BiSAR formation.

Radiometric Terrain Correction Method Based on RPC Model for Polarimetric SAR Data

Radiometric terrain correction (RTC) is an important preprocessing step for synthetic aperture radar (SAR) data application in mountainous areas. At present, the RTC processing of SAR depends on the Range Doppler (RD) positioning model. However, the solution of this model has a high threshold for ordinary remote sensing technicians. To solve this problem, we propose an RTC method based on the rational polynomial coefficient (RPC) model, which is widely used in optical remote sensing and is simpler and more practical than the RD model. China’s GF-3 polarimetric SAR data were used to verify the proposed method. The experimental results showed that the RTC method based on RPC is effective and can achieve better correction effects on the premise of reducing the complexity of the algorithm. The correction effect based on the RPC model can be similar to that based on the RD model. The proposed approach can realize the correction of 4~5 dB terrain radiation distortion to a 0.5 dB level.

A Robust Method for Block Adjustment of UAV SAR Images

To reduce the number of ground control points required for block adjustment of unmanned aerial vehicle (UAV) synthetic aperture radar (SAR) images, a robust block adjustment method is pro-posed. The proposed method aims to solve the problem of unstable adjustment solutions caused by the jittering of UAV SAR platforms. This method is based on the range Doppler model. By analyzing the correlation between the antenna phase center, velocity, and Doppler centroid of the seven orientation parameters, this method performs a block adjustment of UAV SAR images with three orientation parameters: the antenna phase center initial imaging moment, Doppler centroid, and proximity delay. UAV SAR images obtained from an area of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2\times $ </tex-math></inline-formula> 3 km in Dengfeng were used to conduct adjustment experiments. The results obtained using different orientation parameter set-tings verify the robustness and effectiveness of the proposed method. The adjustment results under various control-point layout plans indicate that a uniform layout plan can achieve an adjustment accuracy better than 1 m with a small number of control points.

Geometric calibration of helicopter-borne wide-angle SAR imagery based on the range Doppler model

ABSTRACT Helicopter-borne wide-angle synthetic aperture radar (SAR) can be used in a wide range of military and civil applications because of their high resolution and mobility. The absolute geometric positioning accuracy is an important index for SAR image quality assessment. However, the effectiveness of using traditional geometric calibration methods with helicopter-borne SAR images obtained by time-domain imaging algorithms remains to be verified. Based on the range-Doppler model, a high-precision geometric calibration method for helicopter-borne SAR is proposed in this study and verified by experiments using real data with different resolutions. The results show that after calibration, the positioning accuracy of SAR images with 20 m and 1 m resolutions is improved from 51.33 m to 4.71 m and from 62.49 m to 3.03 m, respectively. These results verify the effectiveness of the proposed method.

Mountainous SAR Image Registration Using Image Simulation and an L2E Robust Estimator

Synthetic Aperture Radar (SAR) is one of the most widely utilized methods to extract elevation information and identify large-scale deformations in mountainous areas. Homologous points in stereo SAR image pairs are difficult to identify due to complex geometric and radiometric distortions. In this paper, a new approach for mountainous area images is suggested. Firstly, a simulated SAR image and a look-up table based on DEM data are generated by a range-Doppler model and an empirical formula. Then, a point matching RPM-L2E algorithm is used to match images obtained by the simulation and in real-time to indirectly obtain the feature points of the real SAR images. Finally, the accurate registration of mountainous areas in the SAR images is achieved by a polynomial transform. Experimental verification is performed by using the data of mountainous SAR images from the same sensor and different sensors. When the registration accuracy of the method is compared with that of two state-of-the-art image registration algorithms, better outcomes are experimentally shown. The suggested approach can effectively solve the registration problem of SAR images of mountainous areas, and can overcome the disadvantages of poor adaptability and low accuracy of traditional SAR image registration methods for mountainous areas.

Combining Optimized SAR-SIFT Features and RD Model for Multisource SAR Image Registration

Multisource synthetic aperture radar (SAR) image registration is a difficult task in remote sensing due to the influence of speckle noise and geometric distortions between the images. The SAR scale-invariant feature transform (SAR-SIFT) is a prior option to extract features for automatic registration of SAR images. However, most registration methods based on the SAR-SIFT operator only use the image information (the geometric distribution of the pixels making up the feature) and do not consider the influences of the side-looking imagery mode and the topographic relief. In this article, we propose a novel registration method to address the above problems, which combines the optimized SAR-SIFT features and the imaging geometry of the SAR system. The major improvement of the algorithm is the use of the range–Doppler (RD) model in feature matching and geometric transformation estimation. A new local matching method aided by the RD model, transforming the global matching mode to the local one, is first introduced to avoid the gross errors and improve the matching efficiency. Then, an RD-model-based geometric transformation model is presented for multisource SAR images with obvious geometric distortions. In addition, the stationary wavelet transform (SWT) is brought in the feature extraction to optimize the SAR-SIFT keypoints to extract reliable and uniformed features. The experimental results fully demonstrate the applicability of the proposed method for registration of multisource SAR images in different acquiring configurations, especially with different passes.

A Fast Algorithm for High Accuracy Airborne SAR Geolocation Based on Local Linear Approximation

Synthetic aperture radar (SAR) is a kind of high-resolution imaging radar, which can work in any weather conditions and is often used for target positioning. Airborne SAR has the advantages of flexible scanning geometry and high spatial resolution compared with Spaceborne SAR, but the quality of SAR image and positioning accuracy is affected by air turbulence and mechanical vibration. In practical applications, it is vital to improve Airborne SAR’s geometric positioning accuracy without ground control points or other reference image information. When positioning a single SAR image with long-range, the Earth surface model is often used as an additional equation to solve the Range-Doppler (RD) model. However, the Earth surface equation is difficult to solve the target height accurately. This study proposed an Airborne SAR target positioning methodology based on a local linear approximation of the Earth surface equation. The proposed local Linear RD (L-RD) model establishes a linear constraint of the local elevation, and the iterative algorithm converges rapidly. To further improve the efficiency of geolocation, we propose a method to directly obtain the initial geolocation used for the iteration based on the geometric relationship. An iterative framework is also proposed to enhance positioning accuracy when DEM is available. The experimental results show that the proposed method can significantly improve the positioning accuracy and reliability of Airborne SAR positioning without control points compared to other methods.

A Robust Stereo Positioning Solution for Multiview Spaceborne SAR Images Based on the Range–Doppler Model

In recent years, the stereo positioning technology based on multiview spaceborne synthetic aperture radar (SAR) images has been widely applied in digital surface model extraction. In this letter, problems of the existing methods based on the range–Doppler (RD) model in a multiview stereo solution are pointed out. A robust stereo positioning solution for multiview spaceborne SAR images based on the RD model is proposed. In the proposed method, the traditional RD model is normalized to reduce the model errors caused by the different scales of the range equation and Doppler equation. A weighting strategy is also proposed to improve the positioning accuracy. This strategy is useful for multiview stereo positioning when using images of different satellites with orbital data of different accuracies. The experiments based on GaoFen-3 and TerraSAR-X satellite data sets validate the effectiveness of the proposed method.

The Impact of SAR Parameter Errors on the Ionospheric Correction Based on the Range-Doppler Model and the Split-Spectrum Method

Interferometric synthetic aperture radar (InSAR) products may be significantly distorted by microwave signals traveling through the ionosphere, especially with long wavelengths. The split-spectrum method (SSM) is used to separate the ionospheric and the nondispersive phase terms with lower and higher spectral sub-band interferogram images. However, the ionospheric path delay phase is very delicate to the synthetic aperture radar (SAR) parameters including orbit vectors, slant range, and target height. In this paper, we get the impact of SAR parameter errors on the ionospheric phase by two steps. The first step is getting the derivates of geolocation with reference to SAR parameters based on the range-Doppler (RD) imaging model and the second step is calculating the derivates of the ionospheric phase delay with respect to geometric positioning. Through the numerical simulation, we demonstrate that the deviation of ionospheric phase has a linear relationship with SAR parameter errors. The experimental results show that the estimation of SAR parameters should be accurate enough since the parameter errors significantly affect the performance of ionospheric correction. The root mean square error (RMSE) between the corrected differential interferometric SAR (DInSAR) phase with SAR parameter errors and the corrected DInSAR phase without parameter errors varies from centimeter to decimeter level with the L-band data acquired by the Advanced Land Observing Satellite (ALOS) Phased Array type L-band SAR (PALSAR) over Antofagasta, Chile. Furthermore, the effectiveness of SSM can be improved when SAR parameters are accurately estimated.

Feasibility of Replacing the Range Doppler Equation of Spaceborne Synthetic Aperture Radar Considering Atmospheric Propagation Delay with a Rational Polynomial Coefficient Model.

Usually, the rational polynomial coefficient (RPC) model of spaceborne synthetic aperture radar (SAR) is fitted by the original range Doppler (RD) model. However, the radar signal is affected by two-way atmospheric delay, which causes measurement error in the slant range term of the RD model. In this paper, two atmospheric delay correction methods are proposed for use in terrain-independent RPC fitting: single-scene SAR imaging with a unique atmospheric delay correction parameter (plan 1) and single-scene SAR imaging with spatially varying atmospheric delay correction parameters (plan 2). The feasibility of the two methods was verified by conducting fitting experiments and geometric positioning accuracy verification of the RPC model. The experiments for the GF-3 satellite were performed by using global meteorological data, a global digital elevation model, and ground control data from several regions in China. The experimental results show that it is feasible to use plan 1 or plan 2 to correct the atmospheric delay error, no matter whether in plain, mountainous, or plateau areas. Moreover, the geometric positioning accuracy of the RPC model after correcting the atmospheric delay was improved to better than 3 m. This is of great significance for the efficient and high-precision geometric processing of spaceborne SAR images.

A New RD-RFM Stereo Geolocation Model for 3D Geo-Information Reconstruction of SAR-Optical Satellite Image Pairs

Nowadays, numerous earth-observation data are obtained from different kinds of platforms, in which data from synthetic aperture radar (SAR) sensors and optical sensors account for the vast majority. They have been widely used in different fields such as 3 dimensional (3D) geo-information reconstruction, object recognition and others. Researchers have investigated the suitability of the rational function model (RFM) for 3D geo-information production with stereo SAR-optical images. Compared with optical remote sensing data, parameters of the RFM for satellite SAR images are not provided to users in most cases, which increases the workload of users applying the SAR-optical stereo geolocation based on RFM. Moreover, the fitting accuracy of RFM to the Range Doppler (RD) model, which is considered as the rigorous sensor model for SAR imagery, do not always meet the requirements. Therefore, a new RD-RFM stereo geolocation model by integrating the RD model of SAR images with the RFM of optical images are proposed for 3D geo-information reconstruction with SAR-optical stereo image pairs. Experiments are conducted based on dataset from Gaofen-3 (GF-3) SAR satellite and Gaofen-2 (GF-2) optical satellite covering urban and mountainous areas in Xinyi City and Dengfeng City, Henan Province, China, respectively. Results indicated that our proposed model can achieve the best performance with different terrain and different convergence angle of stereo SAR-optical image pairs. Compared with the traditional stereo geolocation model based on the RFM for both SAR and optical data, our proposed model is more concise and efficient for the production of 3D geo-information with stereo SAR-optical image pairs, and it's easy to be implemented for users.

New method for airborne SAR image positioning

Synthetic aperture radar (SAR) geometric positioning obtains the geodetic coordinates of each pixel in a SAR image. However, due to the changes in geometry, position and attitude angle of the sensor and the influence factors such as topography, atmospheric refraction, plus the curvature and rotation of the earth, image deformation will occur. Therefore, there is a great practical significance to explore the precise geometric positioning method for SAR images. It proposed a new positioning method combining range-Doppler model and polynomial model, realising SAR image accurate positioning with the digital elevation model data. The method considers the effects of terrain-height-induced geometric distortions and establishes a practical positioning model based on the geometric relationship of imaging. The result shows that the positioning accuracy of the proposed method is higher than the accuracy of the traditional rang-Doppler model and polynomial model with a small number of ground control points.

HYBRID GEOMETRIC CALIBRATION METHOD FOR MULTI-PLATFORM SPACEBORNE SAR IMAGE WITH SPARSE GCPS

Abstract. Geometric calibration is able to provide high-accuracy geometric coordinates of spaceborne SAR image through accurate geometric parameters in the Range-Doppler model by ground control points (GCPs). However, it is very difficult to obtain GCPs that covering large-scale areas, especially in the mountainous regions. In addition, the traditional calibration method is only used for single platform SAR images and can’t support the hybrid geometric calibration for multi-platform images. To solve the above problems, a hybrid geometric calibration method for multi-platform spaceborne SAR images with sparse GCPs is proposed in this paper. First, we calibrate the master image that contains GCPs. Secondly, the point tracking algorithm is used to obtain the tie points (TPs) between the master and slave images. Finally, we calibrate the slave images using TPs as the GCPs. We take the Beijing-Tianjin- Hebei region as an example to study SAR image hybrid geometric calibration method using 3 TerraSAR-X images, 3 TanDEM-X images and 5 GF-3 images covering more than 235 kilometers in the north-south direction. Geometric calibration of all images is completed using only 5 GCPs. The GPS data extracted from GNSS receiver are used to assess the plane accuracy after calibration. The results after geometric calibration with sparse GCPs show that the geometric positioning accuracy is 3 m for TSX/TDX images and 7.5 m for GF-3 images.

Geometric model for high-resolution SAR-GEC images

SAR Geocoded Ellipsoid Corrected (GEC) imagery is often taken as a post product processed from slant or ground range radar images. However, its geometric specific, being corrected to a constant ellipsoid height, makes it a coarse geocoded reference for users who are interested in accurate absolute localisation in applications, such as ‘ortho-image’ generation and digital elevation model (DEM) production. In order to improve the usefulness of SAR GEC imagery, the specific geometric distortions induced by the terrain require corresponding geometric models to perform geometric corrections to the imagery. In this article, both the rigorous physical model and the Rational Polynomial Coefficient (RPC) model for SAR GEC imagery are studied. First, the specific geometry of GEC imagery is illustrated. Then the procedure of reconstructing the rigorous physical model of GECs, which actually is mathematically combined with the normal range–Doppler model, is described in detail. The RPC estimator for replacing this rigorous physical model is then derived. Finally, based on numerous tests with the rigorous physical model available, the modelling error of the RPC is analysed. Four different kinds of high resolution SAR GEC images, i.e. TerraSAR-X, COSMO-SkyMed, RADARSAT-2 and ALOS-PALSAR, are used as experimental data. The experimental results show that using the third-order RPC model with unequal denominators as a substitute for the GEC imaging rigorous physical model, delivers accuracies for different high-resolution SAR GEC images that are all better than 0.01 pixels. The RPC model can be a robust and efficient substitute for the GEC imaging rigorous physical model to perform geometrical processing.

Equivalence Analysis of Accuracy of Geolocation Models for Spaceborne InSAR

There are two main geolocation models for spaceborne synthetic aperture radar (SAR) interferometry (InSAR): range Doppler (RD) and direct geocoding (DG) models. The RD model gets the target position by combining and solving the Doppler equation, slant-range equation, and the modified Earth model equation. The DG location model gets the target position through its 3-D coordinates by the Doppler equation and two slant-range equations. Usually, the geolocation accuracy analyses of these two models are discussed separately. It is confused which one is more precise and we should use during InSAR system designing. This paper deduced and compared the geolocation accuracies of these two models in the same frame-matrix. According to the matrix theory, the explicit expressions of the geolocation uncertainty of RD and DG models were deduced through the use of parameters in matrix form. After defining a new slant-range plane coordinate system, the precision of RD geolocation model and that of geocoding location model were compared quantificationally. It was presented that the geolocation uncertainty formulas between RD and DG models were the same. Then, the conclusion that these two models would lead to the same precision in geolocation measurement was obtained. At last, computer simulation results were employed to confirm the mathematical analysis.

Basic Slant Range–Doppler Modeling of Moving Scatterers for SAR Applications

A fundamental spectral domain model for moving point and distribution of scatterers is presented. The approach is accurate as the spherical phase front is rigorously treated throughout the Doppler analysis. Due to the analytic nature of the model in the range-Doppler plain, large squint-angle operations (e.g., SpotSAR) can be characterized. Furthermore, motion characteristics can be extracted in the subaperture level to better reflect the general motion (e.g., nonuniform). The range-Doppler model can serve as a tool for polarimetric and multichannel analysis.