A robust capon beamformer against uncertainty of nominal steering vector
EURASIP Journal on Applied Signal Processing
Iterative Robust Capon Beamformer
SSP '07 Proceedings of the 2007 IEEE/SP 14th Workshop on Statistical Signal Processing
Direction finding in partly calibrated sensor arrays composed of multiple subarrays
IEEE Transactions on Signal Processing
Robust minimum variance beamforming
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
On robust Capon beamforming and diagonal loading
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Robust adaptive beamforming for general-rank signal models
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
A Competitive Mean-Squared Error Approach to Beamforming
IEEE Transactions on Signal Processing
Direction-of-arrival estimation in partly calibrated subarray-based sensor arrays
IEEE Transactions on Signal Processing
Transmit beamforming for physical-layer multicasting
IEEE Transactions on Signal Processing - Part I
Robust Least Squares Constant Modulus Algorithm to Signal Steering Vector Mismatches
Wireless Personal Communications: An International Journal
Hi-index | 35.68 |
Two new approaches to adaptive beamforming in sparse subarray-based partly calibrated sensor arrays are developed. Each subarray is assumed to be well calibrated, so that the steering vectors of all subarrays are exactly known. However, the intersubarray gain and/or phase mismatches are known imperfectly or remain completely unknown. Our first approach is based on a worst-case beamformer design which, in contrast to the existing worst-case designs, exploits a specific structured ellipsoidal uncertainty model for the signal steering vector rather than the commonly used unstructured uncertainty models. Our second approach is based on estimating the unknown intersubarray parameters by maximizing the output power of the minimum variance beamformer subject to a proper constraint that helps to avoid trivial solution of the resulting optimization problem. Different modifications of the second approach are developed for the cases of gain-and-phase and phase-only intersubarray distortions.