A novel algorithm for mitigating time–frequency aliasing in Doppler through-wall radar

Abstract In recent years, Doppler through-wall radar has been widely used in target localization. However, time–frequency aliasing occurs, which poses a great challenge to the estimation of target parameters. To solve this problem, we propose a novel time–frequency enhancement algorithm. In this paper, we roughly identify the time-frequency features of the interested target component from the time–frequency distribution of the local maximum synchrosqueezing transform and construct a series of discrete demodulation operators that approximate the true properties. Then an optimized window function with adaptive parameters (window width) is designed according to its time–frequency features, which can help effectively compress the echo energy from the selected target component. Finally, an instantaneous frequency (IF) estimator with a local maximum extraction criterion is designed to reduce the noise interference. The experimental results demonstrate that the presented algorithm successfully mitigates time–frequency aliasing, significantly enhancing the accuracy of IF estimation and target localization.