Applications of time-frequency processing to radar imaging

Due to the time-varying behavior of the Doppler frequency of radar returns, and due to the multiple backscattering behavior of radar targets, the resolution of radar images can be significantly degraded and those images may be blurred. Conventional radar processors use the Fourier transform to retrieve Doppler information. To use the Fourier transform properly, some restrictions must be applied: the scatterers must remain in their range cells and their Doppler frequency shifts should be stationary during the entire imaging time. However, due to a target’s complex motion, the Doppler frequency shifts will be timevarying. Therefore, the Doppler spectrum obtained from the Fourier transform will be smeared, and, the radar image will be blurred. However, the restrictions of the Fourier transform can be lifted if the Doppler information is retrieved with a time-frequency transform that does not require a stationary Doppler spectrum. The image blurring problem caused by time-varying Doppler frequency shifts can be solved without resorting to sophisticated motion-compensation techniques. By replacing the conventional Fourier transform with a time-frequency transform, a 2-D range-Doppler Fourier frame becomes a 3-D time-range-Doppler cube. By sampling in time, a time sequence of 2-D range-Doppler images can be viewed. Individual, time-sampled images from the cube provide superior image resolution. When targets contain cavities or ducttype structures, these structures’ scattering mechanisms appear in radar images as blurred ‘‘clouds’’ extending in range. It is beneficial to incorporate the time-frequency transform into range profiles of the radar image. By so doing ‘‘clouds’’ can be removed and structure resonance frequencies identified.