贝叶斯-克里金估计方法在变速成图中的应用

The application of Bayesian-Kriging estimation method in variable velocity mapping.

简述了贝叶斯-克里金估计方法的原理,提出将贝叶斯-克里金估计方法应用于变速成图的思路。具体做法是：将目的层对应的井点速度作为观测数据,对应的地震速度作为猜测数据,对目的层速度进行贝叶斯-克里金估计预测；对估计速度进行时深转换,最终得到区域构造深度图。将该方法应用于塔里木盆地某研究区块的变速成图中,有效提高了该区构造解释精度：在井点位置,估计深度与观测深度的相对误差小于0.4%；在无井控的地方,构造变化比较稳定并符合实际地质情况。应用结果表明，将贝叶斯-克里金估计方法应用于变速成图的思路是可行的。

Through-wall imaging techniques with Ultra-WideBand (UWB) radar are promising candidates for non-destructive detection, especially in disaster areas like calamity rescue scenarios, counter-terrorism and so on. These applications always require high-resolution target imaging to identify the object shape. Based on this requirement, a complex target boundary imaging algorithm for UWB radar is proposed to realize the shape estimation and identification of the target behind walls. As the application is a near field problem, the algorithm offsets the influence from walls using the incident angle of the radar echo calculated by the time-delay difference curve, and estimates the target boundary effectively. Simulation and experimental results of targets behind walls with different shapes show that the proposed algorithm can remove the influence from walls, estimate the target boundary effectively and realize the basic target identification.