Target Trajectory Estimation Algorithm Based on Time–Frequency Enhancement

Abstract

Doppler through-wall radar (TWR) is one of the mainstream target positioning equipment, acquiring the target instantaneous frequency (IF) to achieve trajectory tracking. However, severe time–frequency interference leads to a significant deviation of the estimated trajectory from the actual position. Hence, in this work, we propose a target trajectory estimation algorithm based on time–frequency enhancement. First, the time–frequency analysis (TFA) of the echo signal is carried out by the short-time Fourier transform (STFT). By analyzing the time–frequency distribution (TFD) of the echo signal, an overcomplete time–frequency dictionary is obtained that can reflect the characteristics of the target. Then, the Wigner–Ville distribution (WVD) is employed to process the radar echo signal, and the predefined dictionary is used to suppress the time–frequency interference in the WVD to achieve time–frequency enhancement. Finally, the target IF curve is obtained from the enhanced TFD to synthesize the target motion trajectory. The experiment results show that the proposed method can suppress time–frequency interference and improve the estimation accuracy of IF values. Compared with the existing methods, the proposed method can effectively improve the accuracy of TWR localization.