Study Of Through-the-Wall Imaging Based On Stepped-Frequency-Continuous-Wave Radar

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.