A CA-NCS algorithm in curve trajectory for smart global village

A CA-NCS algorithm in curve trajectory for smart global village
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智慧地球村曲线轨迹CA-NCS算法

DOI:
10.1016/j.scs.2019.101687
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发表时间:
2019-11
影响因子:
11.7
通讯作者:
Qu Tan
Qu Tan
中科院分区:
工程技术1区
文献类型:
--
作者:
Zhang Yan;Qu Tan

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嵌入式系统的发展为处理加速度机动引起的曲线轨迹SAR数据提供了方便。为了消除加速度对成像的影响,提出了一种基于运动补偿的曲线轨迹恒加速度非线性调频缩放(CA-NCS)算法。通过将加速度分为前视加速度和跨航迹加速度,并进一步将其分为垂直于像平面的加速度和像平面内的加速度,采用矢量法对加速度引起的相位误差进行补偿。此外,对于距离徙动,我们通过NCS的方法补偿它的基础上获得的序列反演法(MSR)的准确的二维谱。集成该算法的系统可以处理曲线轨迹的SAR数据,减少计算负担。此外,本文的研究与机器学习的结合将进一步快速识别出具有跨航迹加速度的飞行器的运动曲线,实现实时SAR成像,有助于实现智能地球村中的快速目标定位。
The development of embedded system makes it convenient to process SAR data in curve trajectory which caused by maneuvers with acceleration. To eliminate the effect of acceleration on imaging, a constant acceleration nonlinear chirp scaling (CA-NCS) algorithm in curve trajectory based on motion compensation is proposed. Through dividing the acceleration into forward-looking and cross-track acceleration, which could be divided into the acceleration vertical to the imaging plane and the other one in imaging plane further, we use vectorial methods to compensate the phase errors caused by acceleration. Moreover, for range migration we compensate it through NCS approach based on the accurate 2-D spectrum acquired by the method of series reversion (MSR). The system integrated with this algorithm can process SAR data in curve trajectory and reduce computation burden. In addition, the integration of the research in this paper and the machine learning will further identify the motion curve of the aircraft with cross-track acceleration quickly, and real-time SAR imaging can be realized which helps to achieve fast target localization in smart global village.
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