一种改进的基于全数据集的星载ScanSAR多普勒中心估计方法

An improved doppler centroid estimator for spaceborne ScanSAR based on full datasets

提出一种改进的适合于ScanSAR成像的多普勒中心估计方法.算法首先在各个子带内求得解卷绕的多普勒基带中心估计;随后利用各子带间脉冲重复频率(PRF)的差异,以最小均方误差准则寻找合适的模糊数组合,从而解决多普勒模糊问题.与以往方法不同之处在于,多普勒模糊的解法基于整个回波数据集,而不依赖于相邻子带重叠区数据,且不需要关于信号或噪声分布的先验知识.算法假设子带间的方位向天线指向变化足够小,以致由此导致的多普勒中心的变化远小于PRF的差异,从而可以近似认为多普勒中心是随距离连续变化的.该算法容易实现,并且能有效保证多普勒中心估计的精度和效率.

An improved technique to estimate the Doppler Centroid （DC） for Spaceborne ScanSAR is introduced. The technique estimates unwrapped baseband measures of DC in the subswaths, and then uses PRF （pulse repetition frequency） diversity between different subswaths to solve Doppler Ambiguity by searching proper ambiguity numbers according to the Minimum Mean Square Error （MMSE） rule. This estimator exploits the full datasets but not only the overlap area data, without knowledge about probability distributions of the signals or noises. We assume that changes of azimuth antenna pointing between subswaths are small enough to guarantee that DC changes much tinier than PRF diversity. This algorithm gives efficient and accurate DC estimation, and is easy to implement.