Kernel Design Meets Clutter Cancellation for Irregular Waveforms
conference paper
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 illconditioning
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.
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 illconditioning
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.
TNO Identifier
979497
Publisher
TNO
Source title
IEEE Radar Conference 2023
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