恒加速双基地前视合成孔径雷达扩展场景快速原始数据模拟器

Ziqiang Meng, Yachao Li, M. Xing, Z. Bao
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引用次数: 0

摘要

合成孔径雷达(SAR)原始数据模拟器是进行参数优化和算法测试的重要工具,尤其适用于难以获得真实原始数据的复杂构型。恒加速度双基地前视SAR (BFCA-SAR)是一种新型的特殊成像方式,相对于单静态SAR,它可以对正前方目标进行二维成像,但由于两种平台的速度和加速度都很高,距离历史中存在更复杂的平方根和高阶项。此外,二维频谱相位项的空间方差给回波数据的准确获取带来了困难。提出了一种基于相空间方差定量分析和有效校正的BFCA-SAR场景原始数据快速模拟器。与传统算法相比,该方法具有较高的精度,可以更有效地生成原始数据。
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Fast raw data simulator of extended scenes for bistatic forward-looking synthetic aperture radar with constant acceleration
Synthetic aperture radar (SAR) raw data simulator is an important tool for parameter-optimizing and algorithm-testing, particularly for those complicated configurations in which real raw data is difficult to obtain. As a new and special imaging mode, bistatic forward-looking SAR with constant acceleration (BFCA-SAR) can perform two-dimensional imaging for targets in the straight-ahead position over mono-static SAR. But there exist more complicated square roots and high-order terms in range history owing to high velocities and accelerations from both platforms. In addition, space variances in phase terms of two-dimensional frequency spectrum (2-D FS) make it difficult to gain echo data accurately. In this paper, a fast scene raw data simulator for BFCA-SAR based on quantitative analysis and effective correction of phase space variance is proposed. With high precision, our method can generate raw data more efficiently than traditional algorithms.
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