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

被引:10
作者
Liu, Xuecong [1 ]
Teng, Xichao [1 ]
Li, Zhang [1 ]
Yu, Qifeng [1 ]
Bian, Yijie [1 ]
机构
[1] Natl Univ Def Technol, Coll Aerosp Sci & Engn, Changsha 410073, Peoples R China
基金
中国国家自然科学基金;
关键词
Mathematical models; Synthetic aperture radar; Geology; Earth; Radar polarimetry; Spaceborne radar; Imaging; Digital elevation model (DEM); Levenberg-Marquardt (L-M) method; range-Doppler (RD) model; synthetic aperture radar (SAR); target positioning; SYNTHETIC-APERTURE RADAR;
D O I
10.1109/TIM.2022.3165255
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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.
引用
收藏
页数:12
相关论文
共 30 条
[1]   Not all DEMs are equal: An evaluation of six globally available 30 m resolution DEMs with geodetic benchmarks and LiDAR in Mexico [J].
Carrera-Hernandez, J. J. .
REMOTE SENSING OF ENVIRONMENT, 2021, 261
[2]   Mapping of wheat lodging susceptibility with synthetic aperture radar data [J].
Chauhan, Sugandh ;
Darvishzadeh, Roshanak ;
van Delden, Sander H. ;
Boschetti, Mirco ;
Nelson, Andrew .
REMOTE SENSING OF ENVIRONMENT, 2021, 259
[3]   Accurate Reconstruction and Suppression for Azimuth Ambiguities in Spaceborne Stripmap SAR Images [J].
Chen, Jie ;
Wang, Kai ;
Yang, Wei ;
Liu, Wei .
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2017, 14 (01) :102-106
[4]   The potential of PALSAR RTC elevation data for landform semi-automatic detection and landslide susceptibility modeling [J].
Correa-Munoz, N. A. ;
Murillo-Feo, C. A. ;
Martinez-Martinez, L. J. .
EUROPEAN JOURNAL OF REMOTE SENSING, 2019, 52 (sup1) :148-159
[5]   NASADEM GLOBAL ELEVATION MODEL: METHODS AND PROGRESS [J].
Crippen, R. ;
Buckley, S. ;
Agram, P. ;
Belz, E. ;
Gurrola, E. ;
Hensley, S. ;
Kobrick, M. ;
Lavalle, M. ;
Martin, J. ;
Neumann, M. ;
Nguyen, Q. ;
Rosen, P. ;
Shimada, J. ;
Simard, M. ;
Tung, W. .
XXIII ISPRS Congress, Commission IV, 2016, 41 (B4) :125-128
[6]  
Curlander J. C., 1991, SYNTIC APERTURE R
[7]   LOCATION OF SPACEBORNE SAR IMAGERY [J].
CURLANDER, JC .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 1982, 20 (03) :359-364
[8]  
Daout S., 2021, J GEOPHYS RES-SOL EA, V126, P1
[9]   Improvement and Assessment of the Absolute Positioning Accuracy of Chinese High-Resolution SAR Satellites [J].
Deng, Mingjun ;
Zhang, Guo ;
Cai, Chenglin ;
Xu, Kai ;
Zhao, Ruishan ;
Guo, Fengchen ;
Suo, Jing .
REMOTE SENSING, 2019, 11 (12)
[10]   Improvement of Gaofen-3 Absolute Positioning Accuracy Based on Cross-Calibration [J].
Deng, Mingjun ;
Zhang, Guo ;
Zhao, Ruishan ;
Li, Shaoning ;
Li, Jiansong .
SENSORS, 2017, 17 (12)