SAR imagery of moving targets: application of time-frequency distributions for estimating motion parameters
SAR imagery of moving targets: application of time-frequency distributions for estimating motion parameters
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DOI：
10.1117/12.177719
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发表时间：
1994-06
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影响因子：
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通讯作者：
A. Haimovich;C. D. Peckham;J. Teti
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文献类型：
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作者：
A. Haimovich;C. D. Peckham;J. Teti
众所周知，在合成孔径雷达(SAR)视场内沿航迹运动的目标被成像为散焦目标。由于合成孔径雷达条带图模式被调谐到静止的地面目标上，由于合成孔径雷达处理参数和目标运动参数之间的失配，导致能量溢出到相邻的图像像素，这不仅阻碍了目标特征的提取，而且降低了检测的概率。这个问题可以通过使用与实际目标运动参数匹配的滤波器生成图像来解决，从而有效地将SAR图像聚焦到目标上。对于固定的运动速度，可以从多普勒频率特性的斜率来估计目标速度。该处理在距离压缩数据上但在方位向压缩之前执行。这个问题类似于估计线性调频信号(Chirp)的瞬时频率的经典问题。本文研究了三种不同的时频分析技术在距离压缩合成孔径雷达数据瞬时多普勒频率估计中的应用。特别是，我们比较了Wigner-Ville分布、Gabor展开和短时傅里叶变换在有噪声的SAR数据中的性能。提出了在联合时频域内量化各种方法性能的准则。结果表明，这些方法表现出明显的信噪比阈值效应，即在某一信噪比以下，速度估计的精度迅速恶化。结果还表明，这两种方法在对合成孔径雷达数据的表示上有所不同。
It is well known that targets moving along track within a Synthetic Aperture Radar (SAR) field of view are imaged as defocused objects. The SAR stripmap mode is tuned to stationary ground targets and the mismatch between the SAR processing parameters and the target motion parameters causes the energy to spill over to adjacent image pixels, thus not only hindering target feature extraction, but also reducing the probability of detection. The problem can be remedied by generating the image using a filter matched to the actual target motion parameters, effectively focusing the SAR image on the target. For a fixed rate of motion the target velocity can be estimated from the slope of the Doppler frequency characteristic. The processing is carried out on the range compressed data but before azimuth compression. The problem is similar to the classical problem of estimating the instantaneous frequency of a linear FM signal (chirp). This paper investigates the application of three different time-frequency analysis techniques to estimate the instantaneous Doppler frequency of range compressed SAR data. In particular, we compare the Wigner-Ville distribution, the Gabor expansion and the Short-Time Fourier transform with respect to their performance in noisy SAR data. Criteria are suggested to quantify the performance of each method in the joint time- frequency domain. It is shown that these methods exhibit sharp signal-to-noise threshold effects, i.e., a certain SNR below which the accuracy of the velocity estimation deteriorates rapidly. It is also shown that the methods differ with respect to their representation of the SAR data.