Multi-Rank Adaptive Beamforming with Linear and Quadratic Constraints
Henry L. Cox, Ali Pezeshki, Louis L. Scharf, Olivier Besson, H.C. Lai · 2006
Abstract – Extensions of MVDR and Capon estimation techniques are presented for the situation in which the signal is either rank-one of unknown orientation in a subspace or multi-rank. Only signal-plus-noise snapshots are available. The relationships among linearly and quadratically-constrained approaches are clarified and a unified treatment is given that includes both direct and sidelobe canceller architectures. The unifying component is the multi-rank MVDR beamformer followed by post processing. Detection statistics are presented for the situation in which there is no signal-free training data. Simulations are used to compare rank-one and multi-rank performance. I.