基于GPS-R的双基地SAR移动目标成像方法研究
Bistatic SAR moving target imaging algorithm study based on GPS-R signal
- 2022年26卷第12期 页码:2555-2567
纸质出版日期: 2022-12-07
DOI: 10.11834/jrs.20210378
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纸质出版日期: 2022-12-07 ,
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何振宇,杨扬,陈武,翁多杰.2022.基于GPS-R的双基地SAR移动目标成像方法研究.遥感学报,26(12): 2555-2567
He Z Y,Yang Y,Chen W and Weng D J. 2022. Bistatic SAR moving target imaging algorithm study based on GPS-R signal. National Remote Sensing Bulletin, 26(12):2555-2567
全球导航卫星系统反射GNSS-R(Global Navigation Satellite System Reflectometry)用做双基地合成孔径雷达(简称GNSS-SAR)是近年来新兴的研究方向。当前GNSS-SAR成像的主要对象是地表静态目标,关于动目标成像的研究非常少。本文以全球定位系统GPS(Global Positioning System)卫星作为照射源,提出一种动目标成像方法。该方法首先构建了成像场景的双基地几何模型,推导了一种近似的双基地距离历程,用于描述目标回波的方位向相位变化,然后,采用Keystone变换校正由目标运动引起的未知距离单元徙动;组合短时傅里叶变换和随机抽样一致性算法估计未知的目标移动速度,最后,推导了方位向匹配滤波器用于方位向压缩从而完成动目标成像。采集了两组现场实验数据验证本文方法,实验结果表明:提出的算法能够有效地成像移动目标并且准确地估计目标运动速度、船长度、离岸垂直距离以及移动方向。
Global navigation satellite system reflectometry (GNSS-R) is a typical fusion application of the remote sensing and navigation technology and has become a potential research direction. The use of GNSS-R for constructing a passive bistatic synthetic aperture radar (called as GNSS-SAR) has drawn great attention from the research community in recent years. Current investigations on GNSS-SAR focus on the static objects on land. However
few contributions to the moving target imaging can be found in this novel field. Imaging moving target is a long-standing subject for modern SAR systems. However
traditional GNSS-SAR image formation algorithms cannot be directly applied to the moving target due to the unknown motion. Accordingly
the moving target will be smeared and shifted in the static SAR image. To extend the application of GNSS-SAR
this work selects the global positioning system satellite as the illuminator of opportunity and proposes a frequency domain-based moving target image formation algorithm that has a higher processing efficiency than the traditional time domain-based GNSS-SAR algorithm.
To image a moving target
frequency domain-based algorithm should solve three main problems: (1) The unknown range cell migration induced by the moving target should be corrected. (2) The velocity of the moving target should be estimated. (3) The azimuth compression derivation should be performed due to the bistatic acquisition geometry. To deal with the main problems
this work selects maritime moving ships as the targets of interest and constructs a bistatic acquisition geometry where the receiver and the satellite are stationary during the observation time. Meanwhile
the trajectory of the moving target perpendicular to the line of sight of the receiver antenna is used as a synthetic aperture. An approximate bistatic range history is first deduced to describe the azimuthal phase variation of the target signal based on the bistatic acquisition geometry. A keystone transform is then employed to address the unknown range cell migration
and a method based on short time Fourier transform and random sample consensus is proposed to estimate the velocity. Finally
a derivation of azimuth compression is conducted to accomplish the moving target imaging.
Field experiments were carried out to validate the proposed moving target image formation algorithm. Experimental results show that: (1) The proposed velocity estimation method can obtain the velocity in a low signal-to-noise ratio scene where the least square method cannot work. The fluctuations of the target complex reflectivity will affect the velocity estimation results due to the long observation time
causing errors. However
the errors between the estimated velocities from two groups of the experimental data and the ground truth do not exceed 0.6 m/s. (2) Two targets shown in the SAR image have good accordance with the ground truth in terms of the target-to-receiver vertical distances along the range axis and the ships’ length along the cross-range axis. (3) The designed azimuth matched filter can help in judging the target’s moving direction. Nonetheless
this capability will disappear with the quasi-monostatic configuration. Therefore
the feasibility of the proposed moving image formation algorithm has been confirmed.
The proposed algorithm can be used for monitoring the moving ship target and obtain the target’s velocity
length
vertical distance
and moving direction in the future.
GNSS-RGNSS-SAR动目标成像Keystone变换短时傅里叶变换随机抽样一致性算法
GNSS-RGNSS-SARmoving target imagingKeystone transformshort time Fourier transformrandom sample consensus
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