Inter-atom Interference Mitigation for Sparse Signal Reconstruction Using Semi-blindly Weighted Minimum Variance Distortionless Response
نویسندگان
چکیده
The feasibility of sparse signal reconstruction depends heavily on the inter-atom interference of redundant dictionary. In this paper, a semi-blindly weighted minimum variance distortionless response (SBWMVDR) is proposed to mitigate the inter-atom interference. Examples of direction of arrival estimation are presented to show that the orthogonal match pursuit (OMP) based on SBWMVDR performs better than the ordinary OMP algorithm.
منابع مشابه
A Robust Beamformer Based on Weighted Sparse Constraint
Applying a sparse constraint on the beam pattern has been suggested to suppress the sidelobe level of a minimum variance distortionless response (MVDR) beamformer. In this letter, we introduce a weighted sparse constraint in the beamformer design to provide a lower sidelobe level and deeper nulls for interference avoidance, as compared with a conventional MVDR beamformer. The proposed beamforme...
متن کاملParameter Optimization of the Adaptive Mvdr Qr-based Beamformer for Jamming and Multipath Supression in Gps/glonass Receivers
This paper analyzes the influence of the space-time signal processing technique on the performance of GPS signal acquisition in conditions of strong broadband interference (jamming) and multipath. The space-time processing method used for effective mitigation of GPS interference before processing by a conventional acquisition algorithm is the Minimum Variance Distortionless Response beamforming...
متن کاملImproved OMP Approach to Sparse Multi-path Channel Estimation via Adaptive Inter-atom Interference Mitigation
Since most components of sparse multi-path channel (SMPC) are zero, impulse response of SMPC can be recovered from a short training sequence. Though the ordinary orthogonal matching pursuit (OMP) algorithm provides a very fast implementation of SMPC estimation, it suffers from inter-atom interference (IAI), especially in the case of SMPC with a large delay spread and short training sequence. In...
متن کاملA Nonlinear Adaptive Beamforming Algorithm Based on Least Squares Support Vector Regression
To overcome the performance degradation in the presence of steering vector mismatches, strict restrictions on the number of available snapshots, and numerous interferences, a novel beamforming approach based on nonlinear least-square support vector regression machine (LS-SVR) is derived in this paper. In this approach, the conventional linearly constrained minimum variance cost function used by...
متن کاملVoice-based Age and Gender Recognition using Training Generative Sparse Model
Abstract: Gender recognition and age detection are important problems in telephone speech processing to investigate the identity of an individual using voice characteristics. In this paper a new gender and age recognition system is introduced based on generative incoherent models learned using sparse non-negative matrix factorization and atom correction post-processing method. Similar to genera...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- CoRR
دوره abs/1006.0056 شماره
صفحات -
تاریخ انتشار 2009