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Comparison of practical methods for an efficient FPGA implementation of STAP

机译:高效STAP的FPGA实现的实用方法比较

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In this paper, practical methods for an efficient field programmable gate array (FPGA) implementation of space-time adaptive processing (STAP) are investigated and compared. The most important part for calculating the STAP weights is QR decomposition (QRD) which can be implemented using the modified Gram-Schmidt algorithm. Investigations show the method that uses QRD with less computational burden and leads to more effective implementation. Its structure parameterised with vector size to create a trade-off between hardware and performance factors. For this purpose, the modifications on QRD-MGS are performed in order to speed increasing. Then, the calculation of STAP weight vector was implemented. The implementation results show that decreasing vector size decreases the resources utilisation, computational burden and consumption power. However, computation time increases slightly, but the update rate of the STAP weights is maintained. For example, weights in the system with 6 antenna arrays, 10 received pulses and 200 range samples computed in 262 mu s by vector size of 17 on the Arria10 FPGA the maximum of which is 155 mu s are related to QRD-MGS and 107 mu s is related to other parts. Therefore, QRD-MGS is the most important part in calculation of the STAP weight vector and its simplifying led to an efficient implementation.
机译:在本文中,研究并比较了用于时空自适应处理(STAP)的高效现场可编程门阵列(FPGA)实现的实用方法。计算STAP权重最重要的部分是QR分解(QRD),可以使用改良的Gram-Schmidt算法来实现。研究表明,使用QRD的方法计算量较小,可实现更有效的实施。它的结构使用矢量大小进行参数化,以在硬件和性能因素之间进行权衡。为此,对QRD-MGS进行修改以加快速度。然后,实现了STAP权向量的计算。实施结果表明,减小向量大小会降低资源利用率,计算负担和功耗。但是,计算时间略有增加,但仍保持了STAP权重的更新率。例如,在Arria10 FPGA上,具有6个天线阵列,10个接收脉冲和200个距离样本的系统权重,通过Arria10 FPGA的矢量大小17为262μs计算,最大为155μs,与QRD-MGS和107μs相关。 s与其他部分有关。因此,QRD-MGS是STAP权重向量计算中最重要的部分,其简化导致了高效的实现。

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