Low PRF data aided near-range clutter suppression method

Clutter suppression for non-sidelooking airborne radar is a challenging problem due to the range-dependent clutter. A novel low pulse repetition frequency (low-PRF) data aided prefiltering algorithm in elevation for suppression of the range-dependent near-range clutter is proposed. The developed method obtains the training samples from another elevation-mainlobe-clutter-free low-PRF data, and the adaptive elevation spatial frequency compensation technique is utilized to estimate the covariance matrix. Thus, a desired elevation adaptive pattern can be obtained. Additionally, the clutter rank in elevation domain is derived to provide theoretical guidance for near-range clutter suppression. The performance of the azimuth-Doppler space-time adaptive processing(STAP) can be improved notablely, because the range independency of the training samples for azimuth-Doppler STAP is enhanced after near-range clutter suppression.Numerical examples are given to demonstrate the effecfiveness of the proposed algorithm.