Superior Implementation of Accelerated QR Decomposition for Ultrasound Imaging

In this work, a novel Minimum Variance Distortion less Response (MVDR) beamformer architecture in which the adaptive weight vector is computed based on modified Column wise Givens Rotation (CGR) is presented. As compared to the conventional MVDR beamformer, Quadrature Rotation Decomposition (QRD)-MVDR is suitable for hardware realizations. To improve the real-time performance requirements of the MVDR Beamformer, a parallel pipe-lined CGR based QRD architecture is employed in the adaptive weight computation stage of the MVDR Beamformer. A computationally efficient MVDR beamforming algorithm, which requires to compute only the R matrix in QRD, rather than matrix inverse is used to develop the architecture. The developed architecture generates the adaptive weight vector in 3.9ns, and hence a beam can be formed in 0.25msec time. The designed architecture is implemented using Verilog Register Transfer Level (RTL) coding, and the functional equivalence checking was carried with the Verasonics Vantage-64 Ultrasound Research Platform (URP). The architecture is also ported on Xilinx Kintex-7 FPGA based Emulation set up and validated in real-time, targeting medical ultrasound imaging applications. The developed architecture is compared with the existing architecture implementations. It concludes that the architecture is superior in terms of computational time and can be adapted for ultrafast adaptive beamforming applications.