Monopulse Forward-looking Imaging Based on Doppler Estimation Using Fast Iterative Interpolated Beamforming Algorithm

Abstract

Distinguishing multiple targets in the same resolution cell is an important and challenging task in the forward-looking imaging process of monopulse radar. Although Doppler processing can improve the recognition performance for multiple targets at high squint angles, the precise estimation of Doppler frequency remains challenging under conditions with unknown target numbers and energy leakage from strong point targets. To address these issues, this paper proposes a Fast Iterative Interpolated Beamforming (FIIB) algorithm with model order estimation and single snapshot processing for monopulse forward-looking imaging, which combines information theory to unbiasedly estimate the number of targets and Doppler frequencies. The simulation results show the superiority of the proposed FIIB algorithm over the Chirp-Z Transform (CZT) algorithm for estimating target numbers and Doppler frequencies within the same resolution cell in the presence of multiple point targets. In addition, the proposed FIIB algorithm can accurately estimate point targets beyond a ±5° azimuth angle in monopulse angle measurement tasks. Real-data experiments also reveal that FIIB-based monopulse forward-looking imaging has high focusing capability and imaging contrast and can effectively suppress background clutter.

Keywords

• monopulse radar
• forward-looking imaging
• doppler frequency estimation
• fast iterative interpolated beamforming (fiib) algorithm