  Efficient clutter filtering for pulsed radar systems remains an open issue
when employing pulse-to-pulse modulation and irregular pulse interval waveforms
within the coherent processing interval. The range and Doppler domain should be
jointly processed for effective filtering leading to a large computational
overhead. In this paper, the joint domain filtering is performed by
constructing a clutter projection matrix, also known as the projected
non-identical multiple pulse compression (NIMPC) method. The paper extends the
projected NIMPC filter to irregular pulse interval waveforms. Additionally, a
kernel-based regularization will be introduced to tackle the ill-conditioning
of the matrix inverse of the NIMPC method. The regularization is based on a
model of the second-order statistics of the clutter. Moreover, a
computationally efficient algorithm is formulated based on fast Fourier
transforms and the projected conjugate gradient method. Through a Monte Carlo
study it is demonstrated that the proposed kernelized filtering outperforms the
projected NIMPC in clutter filtering.
