Motion Compensation of Moving Targets for High Range Resolution Stepped-Frequency Radar

High range resolution (HRR) profiling using stepped-frequency pulse trains suffers from range shift and the attenuation/dispersion of range profiles while the target of interest is moving. To overcome these two drawbacks, a new algorithm based on the maximum likelihood (ML) estimation is proposed in this paper. Without altering the conventional stepped-frequency waveform, this algorithm can estimate the target velocity and thereby compensate the phase errors caused by the target ￠ € s motion. It is shown that the velocity can be accurately estimated and the range profile can be correctly reconstructed.