Canceling clutter is an important, but computation-ally intensive part of signal processing in noise radars. It is shown that considerable improvements can be made to a simple least squares canceler if minor constraints are imposed onto noise waveform. The proposed scheme is potentially capable of canceling clutter in real-time, even for high sampling rates.

The problem of cancellation of strong, potentially nonstationary,echoes in noise radars and passive radars utilizing digitaltransmissions is considered. The proposed solution is a multi-stage procedure.Initial clutter estimates, obtained using the least mean squares(LMS) algorithm, are refined using specially designed filters, "matched"to spectral densities of targets and clutter. When the postprocessing filtersare noncausal, the...

Canceling clutter is an important, but very expensive part of signal processing in noise radars. It is shown that considerable improvements can be made to a simple least squares canceler if minor constraints are imposed onto noise waveform. Using a combination of FPGA and CPU, the proposed scheme is capable of canceling both stationary clutter and moving targets in real-time, even for high sampling rates.

The problem of canceling strong clutter echos in a MIMO noise radar is considered. Execution times of three algorithms is compared. The first solution is a standard Least Squares approach employing Cholesky decomposition of the transmitted signal sample autocorrelation matrix. The second approach is based on careful waveform design which guarantees that the signal sample autocorrelation matrix has Toeplitz structure. This enables...

A feedback controller is proposed for cancellation of magnetic resonance imaging (MRI) noise. The design of the controller takes into account specific features of the MRI noise signal. Simulation results show that a considerable rejection rate of the MRI noise can be obtained.