Parallel algorithms and processing architectures for space-time adaptive processing

A. Farina, L. Timmoneri
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引用次数: 9

Abstract

This paper describes methodologies for the on-line calculation of the weights to be used in the linear combination of the received radar data by a set of N antennas and M pulse repetition intervals (PRIs) for the derivation of the adapted space-time filter output. The numerically robust and computationally efficient QR-decomposition is used to derive the so called MVDR (minimum variance distortionless response) and lattice algorithms. Both algorithms are represented as a systolic computational flow graph. The MVDR is able to produce more than one adapted beam focused along different DOAs and Doppler frequencies in the radar surveillance volume. The lattice algorithm offers a computational saving; in fact its computational burden is O(N/sup 2/M) in lieu of O(N/sup 2/M/sup 2/). A comprehensive analysis of the numerical robustness of the algorithms is presented when the CORDIC-algorithm is used to compute the QR decomposition (QRD). Benchmarks on general purpose parallel computers and on a VLSI CORDIC (co-ordinate rotation digital computer) board are presented.
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时空自适应处理的并行算法与处理体系
本文描述了一组N个天线和M个脉冲重复间隔(pri)对接收到的雷达数据进行线性组合时,用于推导自适应时空滤波器输出的权重在线计算方法。利用数值鲁棒性和计算效率高的qr分解导出了最小方差无失真响应(MVDR)和晶格算法。这两种算法都表示为收缩计算流程图。MVDR能够在雷达监视体积中沿不同的DOAs和多普勒频率产生多个适应波束。点阵算法节省了计算量;实际上,它的计算负担是0 (N/sup 2/M)而不是0 (N/sup 2/M/sup 2/)。综合分析了用cordic算法计算QR分解(QRD)时算法的数值鲁棒性。在通用并行计算机和VLSI CORDIC(坐标旋转数字计算机)板上进行了基准测试。
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