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Efficient clutter filtering for pulsed radar systems remains an open issuewhen employing pulse-to-pulse modulation and irregular pulse interval waveformswithin the coherent processing interval. The range and Doppler domain should bejointly processed for effective filtering leading to a large computationaloverhead. In this paper, the joint domain filtering is performed byconstructing a clutter projection matrix, also known as the projectednon-identical multiple pulse compression (NIMPC) method. The paper extends theprojected NIMPC filter to irregular pulse interval waveforms. Additionally, akernel-based regularization will be introduced to tackle the ill-conditioningof the matrix inverse of the NIMPC method. The regularization is based on amodel of the second-order statistics of the clutter. Moreover, acomputationally efficient algorithm is formulated based on fast Fouriertransforms and the projected conjugate gradient method. Through a Monte Carlostudy it is demonstrated that the proposed kernelized filtering outperforms theprojected NIMPC in clutter filtering.

Kernel Design Meets Clutter Cancellation for Irregular Waveforms