线性受限最小二乘恒模波束形成算法

将线性受限条件运用于最小二乘，提出了一种线性受限最小二乘恒模波束形成算法，称为LC-LSCMA，并将它与传统的最小二乘恒模波束形成算法(LSCMA)及预解扩最小二乘恒模波束形成算法(P-LSCMA)进行了仿真比较。仿真结果表明，提出的LC-LSCMA算法比LSCMA及P-LSCMA的信干比性能和误码率性能要好，特别在低信噪比情况下性能仍优于LSCMA。     

基于DOA估计的RLS-CMA算法

恒模算法被广泛地应用到盲自适应波束形成中,除了传输信号波形具有恒定的包络外,恒模算法不需要先验知识。提出一种基于来波方向估计的递推最小二乘恒模算法,基于恒模阵列级联的结构,由递推最小二乘算法决定恒模的初始权向量,同时通过对权向量多项式求根获得下一级的初始权向量,再利用最小二乘恒模迭代几步获得准确的结果。系统可以分离多个同信道信源,在干扰信号较强时,仍有稳定的信干比输出,并对阵列幅相差不敏感。计算机仿真证明了算法的正确性和有效性。     

一种新的多目标盲波束形成技术研究

该文提出了一种新的多目标盲波束形成算法。该方法在最小二乘恒模算法的基础上,通过对一种新的代价函数的最小化,来盲估计波束形成器的权矢量,从而完成对多目标的分离与定向。同时,采用一种改进的神经网络结构解决了最小二乘算法中矩阵求逆的运算,不但能有效提高运行速度,而且易于用硬件实时实现盲波束形成。仿真实验验证了该算法的有效性和正确性。     

用于波束形成的最小二乘广义模值算法研究

对用于波束形成的最小二乘广义模值算法(LSGMA)在多种信号环境下的收敛性能进行了分析;在此基础上提出一种新的多用户盲波束形成算法--迭代最小二乘广义模投影(ILSP-GMA)算法,克服LSGMA算法当恒模干扰信号强于所需信号时会错误收敛的缺陷.仿真结果表明该算法可有效适用于多用户情况,并可获得较原迭代最小二乘投影算法(ILSP)更快的收敛速度.     

一种基于最小Rayleigh熵的盲波束形成算法

提出了一种基于最小Rayleigh熵的盲波束形成算法。该算法根据最小Rayleigh熵的原理对恒模算法的代价函数进行改进,其基本思想就是在寻找最优权矢量时把恒模信号的幅值归并到协方差矩阵里去考虑,以得到最小代价函数的闭式解,从而得到初始权值,最后再用最小二乘恒模算法（LSCMA）算法进行更新迭代。这种算法属于块处理,不存在算法收敛局部极小点和收敛速度慢的问题,所以具有较强的优越性。仿真结果证实了算法的有效性。     

恒模数字波束形成器在多天线软件无线电平台中的实现

在一个多天线软件无线电平台上实现了基于恒模算法(CMA)的数字波束形成器。利用DSP的EDMA传输方式可以提高数据传输的速率,增加波束形成的实时性。试验结果表明:采用恒模数字波束形成算法,可以使天线主波束对准用户信号到达方向,旁瓣或零陷对准干扰信号达到方向,达到抑制干扰的目的。当采样速率为500 kHz时,在我们的平台上可以实时实现数字波束形成。     

线性受限最小二乘恒模盲多用户检测算法

本文将线性受限条件运用于最小二乘恒模算法,提出了一种线性受限最小二乘恒模盲多用户检测算法,称为LCLSCMA,并将它与传统的最小二乘恒模算法(LSCMA)进行了仿真比较。仿真结果表明,本文提出的LCLSCMA算法比传统的最小二乘恒模算法的信干比性能和误码率性能要好,特别在低信噪比强多址干扰情况下性能仍优于LSCMA。     

一种基于天线阵列预处理盲多用户检测算法及其对DOA估计误差的鲁棒性研究

本文提出了一种基于天线阵列的预处理判决反馈最小二乘恒模盲多用户检测算法,称为PDF-LSCMA算法.它是对天线阵列接收信号经预处理,采用判决反馈最小二乘恒模算法进行多用户检测,确保了算法收敛于期望信号.文中就预处理中所用到的波达方向估计误差对PDF-LSCMA算法的影响进行了理论分析,给出了波达方向估计的取值范围,并用计算机仿真对这种算法及分析结果进行了验证.     

块衰落信道下训练序列辅助的恒模多用户检测器研究

恒模算法(CMA)是一种广泛应用于阵列处理、均衡、多用户检测中的盲算法.最小二乘恒模算法(LSCMA)由于其全局收敛性及稳定性受到关注.本文研究块衰落信道下基于训练序列辅助的LSCM算法的性能.本文的研究基于同步CDMA系统,系统中每个用户经历独立的平坦瑞利衰落信道.在发送端,为了在接收端获得数据的信号子空间,目标用户的第一帧中插入少量的训练序列.通过信号子空间信息的辅助,本文提出的训练序列非周期辅助最小二乘恒模(TSA-LSCM-NP,Training Soquence Aided Least Squares Constant Modulus non-periodically)算法在提高少许复杂度的基础上能够获得优于LSCM算法的检测性能.     

ADSP Tiger SHARC 101S在基于最小二乘恒模算法中的应用

对ADSP Tiger SHARC 101S的在最小二乘恒模算法中的应用进行了研究。首先介绍了最小二乘恒模算法基本原理和权值迭代公式，然后介绍了ADSP Tiger SHARC 101S芯片的基本结构特征和他强大的功能，并简单描述了其相应开发软件Visual DSP^ 3．0的功能及使用方法．给出了最小二乘恒模算法实现波束合成的具体流程图，在经过Matlab软件成功进行仿真模拟之后用Visual DSP^ 3.0设计了DSP程序，用C语言嵌套部分汇鳊语言的形式实现了用ADSP Tiger SHARC 101S进行迭代求权向量的过程。     

The constant modulus array for cochannel signal copy and directionfinding

The constant modulus (CM) array is a blind adaptive beamformer capable of recovering a narrowband signal among several cochannel sources without using a pilot or training signal. It is a conventional weight-and-sum adaptive beamformer whose weights are updated by the constant modulus algorithm. An adaptive signal canceller follows the beamformer to remove the captured signal from the array input and to provide an estimate of its direction vector. Based on a Wiener model, we investigate the steady-state properties of the CM array and the signal canceller. For mutually uncorrelated sources and noise, it is shown that the signal canceller exactly removes the source captured by the array. Thus, identical stages of the CM array and signal canceller may be used in a multistage system to recover several cochannel sources. Computer simulations are presented to verify the analytical results and to illustrate the transient behavior of the system     

Steady-state analysis of the multistage constant modulus array

The multistage constant modulus (CM) array is a cascade adaptive beamforming system that can recover several narrowband cochannel signals without training. We examine its steady-state properties at convergence using a stochastic analysis and computer simulations. Based on a Wiener model of convergence for the gradient adaptive algorithms, closed-form expressions are derived for the CM array and canceller weight vectors, as well as the effective source direction vectors at all stages along the cascade system. The signal-capture and direction-finding capabilities of the system are also discussed. Computer simulations for stationary and fading sources are presented to confirm the theoretical results and to illustrate the rapid convergence behavior of the adaptive algorithms     

基于SMI－CMA联合自适应算法的性能分析

恒模算法(CMA)被广泛地应用到盲自适应波束形成中，除了传输信号波形具有恒定的包络外．CMA不需要先验知识。基于SMI—CMA算法的恒模(CM)阵列级联的结构，由SMI算法决定CMA的初始权向量．系统可以分离多个同信道信源，在干扰信号较强时，仍有稳定的SINR输出，具有较好的收敛速度。仿真结果也证明了SMI—CMA算法具有较强的稳健型和较快的收敛速度。     

Minimum-span constant modulus array for a smart antenna testbed

The realisation of an efficient algorithm for a real-time smart antenna testbed based on DECT technology is considered. The testbed is based on a multistage constant modulus array, a blind adaptive beamformer and an adaptive signal canceller that removes the captured signal from the input signals. Based on the Wiener model of convergence, a reduced form of the CM array has been developed that takes advantage of the reduced rank of the input correlation matrix for additional stages. Computer simulations confirm the functionality of this algorithm, and convergence and sensitivity to fading are also discussed.     

Alpha稳定分布噪声下级联恒模阵列及其稳定性分析

该文研究Alpha稳定分布噪声下级联韧性恒模阵列的稳定性。首先,提出一种新型的信号对消器,把本级阵列捕获的信号从接收数据中消除,并分析了该对消器达到的稳定状态。然后,以韧性的波束形成器和新型的信号对消器组成级联恒模阵列。分析了恒模信号和Alpha稳定分布噪声在级联恒模阵列间的传递情况。数值仿真验证了理论分析的结论,并对级联恒模阵列的多信号恢复进行了模拟。     

Misadjustment and tracking analysis of the constant modulus array

The constant modulus (CM) array is a blind adaptive beamformer that can separate cochannel signals. A follow-on adaptive signal canceler may be used to perform direction finding of the source captured by the array. In this paper, we analyze the convergence and tracking properties of the CM array using a least-mean-square approximation. Expressions are derived for the misadjustment of the adaptive algorithms, and a tracking model is developed that accurately predicts the behavior of the system during fades. It is demonstrated that the adaptive canceler contributes more to the overall misadjustment than does the adaptive CM beamformer. Computer simulations are presented to illustrate the transient properties of the system and to verify the analytical results     

A PREPROCESSING LS-CMA IN HIGHLY CORRUPTIVE ENVIRONMENT

A fast preprocessing Least Square-Constant Modulus Algorithm (LS-CMA) is proposed for blind adaptive beamforming. This new preprocessing method precludes noise capture caused by the original LS-CMA with the preprocessing procedure controlled by the static Constant Modulus Algorithm (CMA). The simulation results have shown that the proposed fast preprocessing LS-CMA can effectively reject the co-channel interference, and quickly lock onto the constant modulus desired signal with only one snapshot in a highly corruptive environment.     

Co-channel interference canceller using CMA adaptive array antenna

A co-channel interference canceller that uses a constant modulus algorithm (CMA) adaptive array antenna is presented. In this canceller, when a CMA adaptive array antenna captures a co-channel interference signal, a replica of this signal is generated and then eliminated from a received signal, thus a desired signal can be obtained. Computer simulation results show that the proposed canceller can effectively reduce co-channel interference     

一种基于并联式恒模阵和DOA的同信道信号接收算法

提出一种基于并联式恒模阵和DOA的同信道信号接收算法。采用DOA算法获得信号的波达角，结合初始预测的方法对并联式恒模阵加以初始化，实现对同信道信号的接收和跟踪。它具有无需精确已知信号波达角的特点，克服了已有算法中需要阵列校正的缺陷，同时具有不会误收敛的优点。计算机仿真证实了算法的有效性。