Human Target Localization Using Doppler Through-Wall Radar Based on Micro-Doppler Frequency Estimation
Yipeng Ding, Yinhua Sun, Guo-Wei Huang, Runjin Liu, Xiali Yu, Xuemei Xu
Abstract
Micro-Doppler frequency estimation is an important issue for radar target recognition and localization. In this paper, a novel approach is proposed to accurately estimate the micro-Doppler frequencies of specific target scattering parts, which can be very promising in real-time human sensing applications. For this approach, the Hough transform with a set of Bezier fitting models is first applied to extract the echo component of the human lower leg and accurately estimate their micro-Doppler frequencies. Then, the original echo is demodulated based on the result of micro Doppler frequency estimation, and the echo of leg component is obtained. Finally, the short-time Fourier transform (STFT) algorithm is used to extract the Doppler frequency of the lower leg, and the target trajectory is synthesized by Doppler processing. Compared with the traditional localization algorithm, the proposed approach can greatly improve both the estimation accuracy of the target movement trajectory and the robustness of the Doppler through-wall radar system, and further improve the recognition and tracking targets ability of the system in different situations. Therefore, a series of experiments are conducted to illustrate the performance of the proposed approach.