This paper proposes a new recursive variable loading minimum variance distortionless response (RVL-MVDR) algorithm for robust beamforming in impulsive noise environment. It employs a new method for robust estimation of the sample covariance matrix under impulsive noise and a new method for computing the data-dependent loading level using robust statistics. Computer simulations suggest that the proposed algorithm performs considerably better than the conventional sample matrix inversion (SMI)-MVDR and variable loading (VL) MVDR algorithms in impulsive noise environment.Computer Science, Hardware & ArchitectureComputer Science, Information SystemsEngineering, Electrical & ElectronicCPCI-S(ISTP)
This paper introduces a significant special situation where the noise is a collection of D-plane int...
DoctorThis thesis proposes the various methods to improve the robustness against impulsive measureme...
Subspace tracking is an efficient method to reduce the complexity of signal subspace estimation. Rec...
This paper proposes a new recursive variable loading minimum variance distortionless response (RVL-M...
International audienceMinimum variance distortionless response (MVDR) beamforming (or Capon beamform...
Beamforming algorithm is widely used in many signal processing fields. At present, the typical beamf...
In this work, we introduce a computationally efficient Kalman-filter based implementation of the rob...
This paper proposes a new variable forgetting factor QR-based recursive least M-estimate (VFF-QRRLM)...
We propose a novel algorithm and architecture for minimum variance distortions less response (MVDR) ...
The problem of FIR system parameter estimation has been considered in the paper. A new robust recurs...
A fully-pipelined systolic array for computing the minimum variance distortionless response (MVDR) w...
© 2018 IEEE. A minimum variance distortionless response (MVDR) beamformer can be an effective multi-...
Abstract—A new robust recursive least-squares (RLS) adaptive filtering algorithm that uses a priori ...
A statistical analysis is provided for the sample co-variance matrix of the forward-backward (FB) mi...
A statistical analysis is provided for the sample co-variance matrix of the forward-backward (FB) mi...
This paper introduces a significant special situation where the noise is a collection of D-plane int...
DoctorThis thesis proposes the various methods to improve the robustness against impulsive measureme...
Subspace tracking is an efficient method to reduce the complexity of signal subspace estimation. Rec...
This paper proposes a new recursive variable loading minimum variance distortionless response (RVL-M...
International audienceMinimum variance distortionless response (MVDR) beamforming (or Capon beamform...
Beamforming algorithm is widely used in many signal processing fields. At present, the typical beamf...
In this work, we introduce a computationally efficient Kalman-filter based implementation of the rob...
This paper proposes a new variable forgetting factor QR-based recursive least M-estimate (VFF-QRRLM)...
We propose a novel algorithm and architecture for minimum variance distortions less response (MVDR) ...
The problem of FIR system parameter estimation has been considered in the paper. A new robust recurs...
A fully-pipelined systolic array for computing the minimum variance distortionless response (MVDR) w...
© 2018 IEEE. A minimum variance distortionless response (MVDR) beamformer can be an effective multi-...
Abstract—A new robust recursive least-squares (RLS) adaptive filtering algorithm that uses a priori ...
A statistical analysis is provided for the sample co-variance matrix of the forward-backward (FB) mi...
A statistical analysis is provided for the sample co-variance matrix of the forward-backward (FB) mi...
This paper introduces a significant special situation where the noise is a collection of D-plane int...
DoctorThis thesis proposes the various methods to improve the robustness against impulsive measureme...
Subspace tracking is an efficient method to reduce the complexity of signal subspace estimation. Rec...