Fuzzy inference based robust beamforming
Signal Processing
Multiresolution signal processing techniques for ground moving target detection using airborne radar
EURASIP Journal on Applied Signal Processing
Knowledge-aided STAP processing for ground moving target indication radar using multilook data
EURASIP Journal on Applied Signal Processing
Asymptotic bounds for frequency estimation in the presence of multiplicative noise
EURASIP Journal on Applied Signal Processing
STAP for airborne radar with cylindrical phased array antennas
Signal Processing
Robust adaptive beamforming for large-scale arrays
Signal Processing
Tomographic imaging of dynamic objects with the ensemble Kalman filter
IEEE Transactions on Image Processing
Robust null extension for two-dimensional array antenna
ICACT'09 Proceedings of the 11th international conference on Advanced Communication Technology - Volume 2
A wideband digital beamforming method based on stretch processing
WSEAS Transactions on Signal Processing
Robust Capon beamformer under norm constraint
Signal Processing
Robust constrained least square constant modulus algorithm
IITA'09 Proceedings of the 3rd international conference on Intelligent information technology application
Super-Gaussian loading for robust beamforming
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Adaptive Bayesian beamforming with sidelobe constraint
IEEE Communications Letters
Knowledge-aided multichannel adaptive SAR/GMTI processing: algorithm and experimental results
EURASIP Journal on Advances in Signal Processing - Special issue on advances in multidimensional synthetic aperture radar signal processing
Efficient Radio Transmission with Adaptive and Distributed Beamforming for Intelligent WiMAX
Wireless Personal Communications: An International Journal
Neuro-fuzzy logic in signal processing for communications: from bits to protocols
NOLISP'05 Proceedings of the 3rd international conference on Non-Linear Analyses and Algorithms for Speech Processing
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We unify several seemingly disparate approaches to robust adaptive beamforming through the introduction of the concept of a “covariance matrix taper (CMT)”. This is accomplished by recognizing that an important class of adapted pattern modification techniques are realized by the application of a conformal matrix “taper” to the original sample covariance matrix. From the Schur product theorem for positive (semi) definite matrices and Kolmogorov's existence theorem, we further establish that CMTs are, in fact, the solution to a minimum variance optimum beamformer associated with an auxiliary stochastic process that is related to the original by a Hadamard (Schur) product. This allows us to gain deeper insight into the design of both existing pattern modification techniques and new CMTs that can, for example, simultaneously address several different design constraints such as pattern distortion due to insufficient sample support and weights mismatch due to nonstationary interference. A new two-dimensional (2-D) CMT for space-time adaptive radar applications designed to provide more robust clutter cancellation is also introduced. Since the CMT approach only involves a single matrix Haddamard product, it is also inherently low complexity. The practical utility of the CMT approach is illustrated through its application to both spatial and spatio-temporal adaptive beamforming examples