【作者】 王涵宁；

【导师】 周智敏； 陆必应；

【作者基本信息】 国防科学技术大学 ， 信息与通信工程， 2011， 硕士

【摘要】 穿墙雷达能够穿透墙壁等障碍物,对隐蔽目标进行探测,因而在灾后救援、反恐维稳等方面具有广泛的应用前景。实现墙后目标的高精度成像是提升穿墙雷达探测性能的关键,然而电磁波在建筑物内传播不可避免存在衰减、多径、色散和折射等现象,致使传统的成像方法难以取得理想的效果。本文以某步进频连续波穿墙雷达人体目标成像探测实测数据处理为应用背景,重点研究抑制墙体杂波高精度成像和人体目标检测技术,主要工作如下:1、建立了步进频穿墙雷达回波信号的了简化模型,分析了墙体折射对目标回波时延的影响,在此基础上对传统的BP成像算法进行了改进,使其适用于墙后区域目标成像。2、利用人体目标慢速运动特征,提出先在回波域差分处理抑制墙体杂波,再利用BP算法进行运动目标成像。该方法应用于实测数据,实现了对慢速运动人体目标的有效成像。3、在高频假设下利用反射系数与透射系数对墙体的电磁特性进行了进一步建模,并根据透射系数构造了补偿因子,以此校正目标位置,实现目标的重聚焦。在墙体参数未知的情况下,提出了一种基于图像熵估计墙体参数、实现墙后目标位置校正和高精度聚焦的方法。仿真和实测数据处理结果证明了该方法的有效性。4、采用霍夫变换识别并削弱墙体残余,使得目标质量进一步提高。根据目标与背景在图像中的幅值分布,采用自适应检测的方法实现目标检测,并采用形态滤波来改善检测中的虚警、漏报现象。本文研究的的成像技术和相关处理方法均成功应用于某穿墙雷达的实测数据处理。更多还原

【Abstract】 Through-the-wall (TTW) radar is widely applied in both civilian and military field for its capacity to penetrate building barricades and detect interior targets. Interior target imaging with high accuracy is the effective way to enhance TWR’s detection ability. However, traditional radar imaging approaches can not achieve ideal effect due to the attenuation, multipath, dispersion and refraction of electromagnetic wave when it travels inside of the building. In this paper, a human behind the wall is detected by the stepped-fequency-continuous-wave (SFCW) radar. Based on the field data, the research is concentrated on wall clutter suppression and accurate target imaging. The major work is as follows:1. The influence of wall refraction on target echo’s time delay is discussed according to the simplified echo model. Based on the conclusion, the traditional BP algorithm is modified for TTW imaging.2. A wall clutter suppression algorithm based on time-domain difference is proposed by using the characteristic of slow-moving target. Experimental results show that this algorithm is able to image the human target moving behind the wall.3. High frequency electromagnetic characteristics of the wall are further modeled, and the compensation coefficient is constructed for target refocusing. In order to refocus target imaging when wall parameters are unknown, a refocusing method based on image entropy measurement is proposed. Experiment and simulation results demonstrate that, this method can realize target refocusing and wall parameter estimation simultaneously.4. In order to improve the image quality, Hough transformation is adopted to recognize and undermine wall remnants. Stastical results show that, pixel values of the target and the background clutter follow different propability distributions. Based on this conclusion, an adaptive target detection method is applied. Finally, the morphaligical filtering is adoppted to surpress the false alarms and miss detections.The technologies of TTW imaging proposed in this paper are all successfully applied to the field data processing.更多还原