A framework for reduced dimension robust Capon beamforming
Samuel D. Somasundaram · 2011
Recent robust Capon beamformers (RCBs) systematically allow for array steering vector (ASV) errors by exploiting ASV uncertainty ellipsoids, which are typically characterized in element space (ES). Reduced dimension (RD) techniques are often used to reduce computational complexity and speed up algorithm convergence. Here, a general framework is proposed for combining RD and RCB techniques, producing RD-RCBs. The key to this framework is a complex propagation theorem, which propagates the ES ellipsoid through the dimension reducing transform, so that the appropriate ASV uncertainty information is exploited in the RD space.