Description: 本文提出一种新的相干波束形成方法，利用内插变换对相干背景下的真实阵列进行虚拟平移，得到多个虚拟平移后的信号协方差矩阵；对其进行平均后，所得到的相干信号协方差矩阵具有满秩性。利用一般的波束形成法求出最优权向量。该方法解决了五阵元均匀圆阵下二维相干信号的波束形成问题。-This paper presents a new coherent beamforming methods, the use of interpolation transform the context of coherent arrays of virtual real translation, from a number of virtual post-translational signal covariance matrix their average after by Coherent signal covariance matrix has full rank of. Beamforming using the general method to derive the optimal weight vector. The method to solve a five-element uniform circular array of two-dimensional signals coherent beamforming problem. Platform: |
Size: 1330176 |
Author:关成 |
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Description: 实现对自适应波束形成SIM算法的仿真，在该程序中，我们先设置入射的信号，再进行互协方差矩阵和自协方差矩阵的求解来实现该算法-To achieve adaptive beamforming algorithm for the simulation of SIM, in the process, we first set up the incident signal and then cross-covariance matrix and covariance matrix from the solution to the realization of the algorithm Platform: |
Size: 1024 |
Author:张琴超 |
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Description: 块自适应处理算法先有采样快拍数据计算采样协方差矩阵，再来计算自适应权矢量。典型的块自适应处理算法为采样矩阵求逆(SMI)算法。仿真了采样矩阵求逆法(SMI)的波束形成方向图旁瓣的高低受信号快拍数的影响。-Block adaptive processing algorithms prior sample snapshot data of the sampling covariance matrix, again computing adaptive weight vector. A typical block adaptive processing algorithms for the sample matrix inversion (SMI) algorithm. Simulation of the sampling matrix inversion method (SMI) beamforming pattern sidelobe level of the signal by the number of snapshots. Platform: |
Size: 1024 |
Author:Billy |
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Description: 最大信噪比准则方向图和功率谱；
ASC旁瓣相消—MSE准则；
线性约束最小方差(LCMV)准则；
不同方法估计协方差矩阵的Capon波束形成；多点约束的Capon波束形成和方向图-Pattern and the power spectrum of the maximum signal to noise ratio criteria ASC sidelobe cancellation-the MSE criteria Linearly constrained minimum variance (LCMV) criterion Different ways to estimate the covariance matrix of the Capon beamforming Multi-point constraints Capon beamforming and pattern； Platform: |
Size: 26624 |
Author:刘晓 |
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Description: 波束空间MUSIC算法源程序.针对这种算法存在的分辨力差、估计偏差大等缺陷提出了一种新的基于波束空间的单次快拍MUSIC算法该方法首先利用单次快拍来估计阵列数据的协方差矩阵再将常规波束形成-Beam space MUSIC algorithm source code for this algorithm resolution, with an estimated deviation defects based on a single snapshot of the beam space MUSIC algorithm is the first to use a single snapshot to the estimated array data covariance matrix of the then conventional beamforming Platform: |
Size: 1024 |
Author:王刚 |
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Description: 提出一种基于直接数据域最小二乘方法的自适应多波束形成算法,包括前向计算、后向计算和前-
后向计算。利用天线阵元输出复电压的单快拍数据构建矩阵方程,采用共轭梯度法求解得到阵列的自适应权值向
量,从而在所有期望信号方向形成接收波束,同时在各干扰方向形成深零陷,使信干噪比显著提高。由于只需对单
快拍数据进行处理,并且避免了样本协方差矩阵的构造及矩阵求逆运算,故计算复杂度较传统算法低。-An adap tive multip le beamforming algorithm based on D3LS ( direct data domain least squares) app roach is
p resented in this paper, including forward p rocedure, backward p rocedure and forward2backward p rocedure. A single snap2
shot data of the comp lex voltagesmeasured at array elements is used to form the matrix equation, which is solved with the
conjugate gradientmethod to obtain the adap tive weight vector of array. Finally, beams are formed along the DOAs ( direction
of arrival) of SO Is ( signal of interest) and deep nullings are made along the DOAs of interferences to imp rove the SINR ( sig2
nal2to2interference2p lus2noise ratio) greatly. The p roposed algorithm has a lower computation comp lexity than conventional al2
gorithms as it p rocesses only a single snap shot data as opposed to forming the samp le covariance matrix and performingmatrix
inversion operation. Platform: |
Size: 323584 |
Author:拉拉 |
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Description: 不同方法估计协方差矩阵的Capon波束形成,以及多点约束的Capon波束形成和方向图，自己运行效果很好。-Different methods of estimation covariance matrix Capon beamforming, and multi-point constraints Capon beamforming and direction maps, run their own good results. Platform: |
Size: 1024 |
Author:小屯 |
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Description: 现有的向量加权稳健波束形成方法只有在指向误差较小的情况下才能有效估计目标的信号功率；矩阵加权波束形成方法在指向误差较大时，虽然可以估计目标的信号功率，但是它的系统实现复杂度与向量加权稳健波束形
成方法相比较大。针对以上问题，该文提出基于半正定秩松弛(SDR)方法的稳健波束形成，该方法优化模型中的目标函数与Capon 算法的目标函数相同，优化变量为加权向量的协方差矩阵，并约束方向图的主瓣幅度波动范围、旁瓣电平，协方差矩阵的秩为1。-The existing vector weighted robust beamforming is able to estimate the signal power of target only in
situations of a small steering angle error. For a larger steering angle error case, although the matrix weighted
beamforming can effectively estimate the signal power of the target as well, the system implementation is more
complicated than above mentioned vector weighted. In order to solve these problems, this paper presents a new
robust beamforming approach based on SemiDefinite rank Relaxation (SDR). Detailed description of the proposed
method are given as follows: the optimal model has the same objective as that of the Capon algorithm the
optimization variable is the covariance matrix of weight vector with constraints posed on the ripple of mainlobe
amplitude and sidelobe level, and the rank of covariance matrix is 1. Platform: |
Size: 688128 |
Author:treedev |
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