FPGA实现基于施密特正交化的自适应算法

在自适应波束形成算法理论基础上,将修正施密特正交化算法运用在基于三角分解的样本矩阵求逆算法中,提出了基于修正施密特正交化算法的三角分解矩阵求逆算法,并给出了具体的可编程门阵列硬件实现结构。该硬件结构的实现采用了坐标旋转数字计算机代替该算法中的除法运算,有效地节约了硬件资源消耗和结构时延。通过硬件仿真对计算结果进行分析研究,实验证明该硬件结构不仅有良好的数值稳定性,能对干扰有效抑制,且硬件资源消耗少,高度模块化。     

改进的矩阵求逆的FPGA设计和实现

通过对上三角矩阵求逆算法的研究,提出一种优化的适合FPGA实现的并行求逆的结构,并运用Verilog硬件描述语言对其建模,通过硬件仿真工具QuartusII对其进行编译仿真,仿真结果表明,改进的并行结构能够在n个时钟周期内完成n阶上三角矩阵的求逆。     

基于FPGA的Cholesky分解矩阵求逆

针对在空时自适应处理(STAP)中通常采用Cholesky分解矩阵求逆算法求杂波协方差矩阵的逆矩阵,设计了基于FPGA的并行化Cholesky分解矩阵求逆运算模块的实现架构。该模块分成Cholesky分解子模块、三角矩阵求逆子模块和三角矩阵相乘子模块等三部分,流水执行求逆运算。通过实测与仿真,对矩阵阶数、运算并行度、FPGA占用资源、运算时间和运算精度等要素之间的关系进行了详细分析。     

基于FPGA实现快速矩阵求逆算法

Cholesky分解是一种矩阵运算方法。相比传统的矩阵求逆算法,它能够大大简化矩阵求逆的运算量,提高实时性。因此,介绍Cholesky分解原理及方法,并根据这一特性,在FPGA中实现基于Cholesky分解的快速矩阵求逆算法。FPGA具有流水线设计的特点,能够进一步提高接收抗干扰处理的实时性。用Matlab对FPGA实现的各种矩阵规模数据进行仿真,根据仿真结果和FPGA实际资源选取最优的FPGA实现方案。     

基于脉动阵的自适应波束形成算法仿真

为了满足自适应波束形成技术对实时性的要求,将脉动阵应用于波束形成算法中,以实现自适应权向量的实时获取.通过对QR分解采样矩阵求逆算法、混合型QR分解采样矩阵求逆算法和逆QR分解采样矩阵求逆算法的理论分析,利用脉动阵,对输入数据矩阵进行QR分解,得到旋转因子,实现自适应权向量的实时更新.针对三种算法各自的脉动阵进行仿真,结果表明,基于脉动阵的自适应波束形成算法实现了权向量的高速获取,并为后续的工程实践提供了理论依据.     

基于QR分解算法的任意阶复矩阵求逆的DSP实现

常用的矩阵求逆方法不易于工程实现,计算软件也无法装备到电子系统中去,文中采用QR分解算法实现了基于ADSP TS201S DSP汇编语言的矩阵求逆。该方法克服了高阶矩阵不易求逆,且效率不高的缺点,实现了任意阶复矩阵的快速求逆运算。仿真结果表明,对于16阶的复数矩阵,该工程方法的计算效率能达到μs级,计算精度能达到10^-4量级。     

基于Verilog的下三角矩阵求逆设计与实现

矩阵运算广泛应用于各类电路计算中,矩阵运算的硬件实现能够充分发挥硬件的速度和并行性,其中矩阵求逆是矩阵运算中重要的运算.根据矩阵求逆算法的基本思想,本文提出了一种最大阶数可达16 × 16的矩阵求逆方案,通过硬件描述语言verllog建模,用Design Compile进行综合及进行modelsim仿真,仿真结果表明这...     

任意维矩阵求逆的FPGA设计与实现

矩阵运算广泛应用于各类电路计算中,矩阵运算的硬件实现能够充分发挥硬件的速度和并行性。其中矩阵求逆是矩阵运算中重要的运算,针对目前多维矩阵难以设计的情况,本文提出了一种任意维矩阵求逆的硬件实现方法,实验达到了预期目标。任意维矩阵求逆的硬件实现在数字信号处理领域将具有广泛的应用前景。     

一种基于约化因子上三角矩阵求逆的FPGA实现方法

矩阵运算广泛应用于实时性要求的各类电路中，其中矩阵求逆运算最难以实现。基于现场可编程门阵列(FPGA)实现矩阵求逆能够充分发挥硬件的速度与并行性优势，加速求逆运算过程。基于改进的脉动阵列的计算架构，采用一种约化因子求逆的优化算法，将任意一个n×n阶上三角矩阵转换成对角线为1的上三角矩阵，使得除法运算与乘加运算分离开来，大大简化矩阵求逆运算过程。以一个4×4阶上三角矩阵求逆为例，在Xilinx ISE平台下，采用Virtex5 FPGA完成算法实现与功能验证，在14个周期内，使用了2个除法器，3个乘法器与4个加法器实现整个矩阵求逆运算。相比于经典的脉动阵列架构，仅占用近一半资源的同时，性能提升了26.43%；相比于集成更多处理单元(PE)的脉动阵列实现方式，在性能近乎不变的情况下，耗费的资源缩减到1/4，大幅度提升了资源利用率。     

三角矩阵求逆的ASIC实现研究

通过分析上三角矩阵的求逆算法，提出了一种适合ASIC实现的心动阵列结构，并用VHDL语言对其进行描述，最后通过Synopsys的Design Compile和Cadence的NC—Sim对其做综合后仿真验证了其正确性。仿真结果表明这种并行结构能够正确计算出上三角矩阵的逆矩阵。     

基于GF(2~m)的椭圆曲线求逆算法的改进研究

针对二进制域上现有求逆算法计算量大、并行度小、速度慢的缺点进行改进,基于二元Euclidean算法提出了改进,设计了相应的乘法器硬件结构,并且分析了其运算效能和资源占用情况。将此求逆计算器的并行改进算法使用Verilog语言编程实现,利用Xilinx ISE 12.4对整个求逆算法综合仿真(行为级),在Xilinx Virtex-5 XC5VFX70T的硬件平台上验证求逆算法的运算效率,结果表明对求逆算法的改进有效地提高了求逆运算的速度。     

一种新的应用于并行数字仿真的电路划分算法

为减少仿真的时间,并行仿真技术广泛应用于大规模集成电路的计算.研究发现为并行仿真所做的电路划分对提高仿真速度有相当重要的作用.该文提出一个新的多层启发式的拓扑电路划分算法,展示了将该算法应用于一个实际的电路并行仿真系统(Discovery)所获得的仿真加速.该算法主要着眼于平衡计算负载,减少整个仿真网络通信量这两方面来提高仿真系统的性能.试验结果表明该算法比其他的电路划分算法取得了更好的性能提高.     

A fast CFAR detection space-time adaptive processing algorithm

All of the conventional CFAR detection algorithms that use space-time processing involve a time-consuming matrix-inversion operation. Based on today's technology, this computational complexity sometimes makes the full-rank solution difficult to realize. In this correspondence, a CFAR detection algorithm, which does not need a matrix inversion, is developed by an adaptation and extension of Hotelling's principal-component method studied recently by Kirsteins and Tufts (1994). Finally, the performance of the new CFAR test statistic is analyzed, and the effect of the rank reduction on performance is evaluated for an example scenario     

基于有符号数字系统的Montgomery模逆算法及其硬件实现

 在椭圆曲线密码中,模逆运算是有限域运算中最复杂、最耗时且硬件实现难度最大的运算.本文在Kaliski算法的基础上,提出了基于有符号数字系统的Montgomery模逆算法,它支持素数域和二进制域上任意多精度参数的求模逆运算.据此算法,设计了相应的硬件结构方案,并给出了面积复杂度和时间复杂度分析.仿真结果表明,相比于其它模逆算法硬件设计方案,本文提出的基于有符号数字系统的Montgomery模逆算法在运算速度、电路面积、灵活性等方面具有显著的优越性.     

基于STM32的无刷直流电机控制器硬件电路设计及实验研究

以STM32F103C8T6为核心,设计了无刷直流电机控制器硬件电路。电路主要包括IR2310构成的PWM驱动电路、IRF3808构成的逆变电路、增量式旋转编码构成的速度反馈电路。控制器具有CAN和RS232通信接口,可与计算机或PLC构成速度或位置伺服系统。利用由xPC目标搭建的半实物仿真平台对PI参数进行整定。测试了控制器的速度伺服响应性能,给定速度为2400rpm时,控制器响应时间为0.32s。实验结果表明,系统工作可靠,稳定性好,响应速度快,可以满足上肢康复机器人要求。     

大气激光通信中垂直分层空时码的研究与实现

针对垂直分层空时(V-BLAST)码存在译码复杂度高、误码性能不理想等不足,本文将串行干扰消除(SIC)算法应用于V-BLAST码的译码中,提出了一种适合于大气激光通信的分层空时(LST)编码方案。采用仿真分析和硬件实验相结合的方法,验证了本文方案的正确性和合理性。实验结果证明了在大气激光通信中采用基于SIC算法的V-BLAST编码的可行性,为进一步提高通信的传输速率、改善系统性能提供了新方法和依据。     

Rain Attenuation and Doppler Shift Compensation for Satellite Communications

In high‐speed multimedia satellite communication systems, it is essential to provide high‐quality, economical services by using efficient transmission schemes which can overcome channel impairments appearing in the satellite link. This paper introduces techniques to compensate for rain attenuation and the Doppler shift in the satellite communication link. An adaptive transmission technique with a control algorithm to adaptively allocate transmission schemes is used as a countermeasure to rain attenuation. We introduce a new rain attenuation modeling technique for estimating system performance and propose a novel Doppler shift compensation algorithm with reduced hardware complexity. Extensive simulation results show that the proposed algorithm can provide greatly enhanced performance compared to conventional algorithms. Simulation software and hardware which incorporate the proposed techniques are also demonstrated.     

Maximum likelihood parameter and rank estimation in reduced-rankmultivariate linear regressions

This paper considers the problem of maximum likelihood (ML) estimation for reduced-rank linear regression equations with noise of arbitrary covariance. The rank-reduced matrix of regression coefficients is parameterized as the product of two full-rank factor matrices. This parameterization is essentially constraint free, but it is not unique, which renders the associated ML estimation problem rather nonstandard. Nevertheless, the problem turns out to be tractable, and the following results are obtained. An explicit expression is derived for the ML estimate of the regression matrix in terms of the data covariances and their eigenelements. Furthermore, a detailed analysis of the statistical properties of the ML parameter estimate is performed. Additionally, a generalized likelihood ratio test (GLRT) is proposed for estimating the rank of the regression matrix. The paper also presents the results of some simulation exercises, which lend empirical support to the theoretical findings     

Lower bounds for parametric estimation with constraints

A Chapman-Robbins form of the Barankin bound is used to derive a multiparameter Cramer-Rao (CR) type lower bound on estimator error covariance when the parameter &thetas;∈Rⁿ is constrained to lie in a subset of the parameter space. A simple form for the constrained CR bound is obtained when the constraint set Θ_C, can be expressed as a smooth functional inequality constraint. It is shown that the constrained CR bound is identical to the unconstrained CR bound at the regular points of Θ_C, i.e. where no equality constraints are active. On the other hand, at those points &thetas;∈Θ_C where pure equality constraints are active the full-rank Fisher information matrix in the unconstrained CR bound must be replaced by a rank-reduced Fisher information matrix obtained as a projection of the full-rank Fisher matrix onto the tangent hyperplane of the full-rank Fisher matrix onto the tangent hyperplane of the constraint set at &thetas;. A necessary and sufficient condition involving the forms of the constraint and the likelihood function is given for the bound to be achievable, and examples for which the bound is achieved are presented. In addition to providing a useful generalization of the CR bound, the results permit analysis of the gain in achievable MSE performance due to the imposition of particular constraints on the parameter space without the need for a global reparameterization