Indoor Target Localization Using Through-Wall Radar Based on the Time-Frequency Enhancement Algorithm

The use of Doppler through-wall radar (TWR) in the field of indoor target localization has attracted extensive attention due to its advantages in medium penetration, positioning accuracy, and strong anti-interference ability. However, in multitarget positioning, the echo signal consists of multiple components, leading to time-frequency aliasing in the time-frequency distribution (TFD) when using short-time Fourier transform (STFT) for time-frequency analysis (TFA). This aliasing complicates the accurate estimation of the target's instantaneous frequency (IF) curve, thus affecting the target positioning accuracy. To tackle these problems, we propose a time-frequency enhancement algorithm that obtains a highly concentrated TFD, suppressing time-frequency aliasing and noise, particularly for signals with intersecting or adjacent IF curves. The proposed method employs the time-frequency enhancement network (TFE-Net) to learn the time-frequency features of the real and imaginary parts of STFT results under different window lengths, resulting in a TFD without time-frequency aliasing and with concentrated time-frequency energy. Subsequently, the target IF curve is estimated from the enhanced TFD to achieve target tracking. Multitarget tracking experiments demonstrate that the proposed method, compared with existing methods, not only effectively suppresses time-frequency aliasing and improves time-frequency energy concentration but also enhances the radar system's positioning accuracy.