Doppler through-wall radar target localization based on local optimum time–frequency chirp reassignment

Abstract Doppler Through-Wall Radar has demonstrated considerable promise in non-contact target localization, particularly in complex indoor environments. However, when multiple moving targets are present, their echo signals often contain closely spaced or intersecting instantaneous frequency (IF) components. These characteristics introduce substantial challenges for conventional time–frequency analysis methods. This paper proposes a novel algorithm, local optimum time–frequency chirp reassignment (LOFCR), to address this issue. The method begins with a Short-Time Fourier transform (STFT) for initial time–frequency representation, followed by region segmentation based on energy concentration to extract representative local features. A chirplet basis-based local synchronization strategy is then introduced to perform high-dimensional reassignment in both frequency and chirp domains, enhancing resolution and reducing time–frequency aliasing phenomenon. Experimental results demonstrate that LOFCR significantly improves IF estimation and target localization accuracy compared to traditional methods.