Research for quasi-far field and super-resolution radar imaging method for autonomous mobile robot

本研究旨在发展超宽带雷达的准远场超分辨成像技术。超宽带雷达是有前途的创新测量技术的救援或资源勘探自主机器人，在光学传感器不能应用。虽然我们已经开发了原始的超分辨率和阴影区域成像方法，该方法面临的困难，目标识别的情况下，获得的孔径尺寸不足，其中包括我们的方法的传统方法遭受的成像区域不足。为了解决上述问题，我们已经开发了几种新的方法，基于数据空间的椭圆拟合方法，图像扩展方法使用多次散射信号，运动目标成像方法使用多基地观测模型，图像扩展方案利用全极化数据，并通过数值模拟的验证。

This research project aims at developing the quasi-far field and super-resolution imaging techniques for UWB radar. The UWB radar is promising for innovative measurement technique for rescue or resource exploration autonomous robots, where the optical sensor cannot be applied. While we have developed the original super-resolution and shadow region imaging method, this method faces the difficulty for target recognition in the case that an insufficient aperture size is obtained, where the conventional methods including our methods suffers from an insufficient imaging region. To solve the above problem, we have developed several novel approaches, based on the ellipse fitting method on data space, image expansion method using multiple scattering signal, moving target imaging method using multistatic observation model, image expansion scheme exploiting full polarimetric data, and their validations have been achieved through the numerical simulations.