图示了麦克风阵列波束成形以在干扰优势，嘈杂的环境中提取所需的语音信号。这种操作可用于增强感知或进一步处理的语音信号质量。例如，嘈杂的环境可以是交易室，麦克风阵列可以安装在交易计算机的监视器上。如果交易计算机必须接受来自交易者的语音命令，则波束形成器操作对于增强接收的语音质量并实现设计的语音识别精度至关重要。

Model a point-to-point MIMO-OFDM system with beamforming. The combination of multiple-input-multiple-output (MIMO) and orthogonal frequency division multiplexing (OFDM) techniques have been adopted in recent wireless standards, such as 802.11x families, to provide higher data rate. Because MIMO uses antenna arrays, beamforming can be adopted to improve the received signal to noise ratio (SNR) which in turn reduces the bit error rate (BER).

示出了如何将数字波束成形应用于由天线阵列接收的窄带信号。示出了三个波束成形算法：相移波束形成器（相控），最小方差失真响应（MVDR）波束形成器，以及线性约束的最小方差（LCMV）波束形成器。

Illustrates using beamscan, MVDR, and MUSIC for direction of arrival (DOA) estimation. Beamscan is a technique that forms a conventional beam and scans it over directions of interest to obtain a spatial spectrum. Minimum variance distortionless response (MVDR) is similar to beamscan but uses an MVDR beam. Multiple signal classification (MUSIC) is a subspace method that provides high resolution DOA estimates. For all three methods, the peaks of the output spatial spectrum indicate the DOAs of the received signals. In this example, we illustrate the use of beamscan, MVDR, and MUSIC to estimate broadside angles with a uniform linear array (ULA) and azimuth and elevation angles with a uniform rectangular array (URA).

Illustrates several high-resolution direction of arrival (DOA) estimation techniques. It introduces variants of the MUSIC, root-MUSIC, ESPRIT and root-WSF algorithms and discusses their respective merits in the context of far-field, narrowband signal sources received by a uniform linear array (ULA) antenna.

Introduces how forming a virtual array in MIMO radars can help increase angular resolution. It shows how to simulate a coherent MIMO radar signal processing chain using Phased Array System Toolbox™.

简要介绍了时空自适应处理（STAP）技术，并说明了如何使用相控阵系统工具箱™将STAP算法应用于接收的脉冲。STAP是一种用于机载雷达系统的技术，以抑制杂波和干扰干扰。

使用广义互相关（GCC）和三角测量来确定宽带信号源的位置。为简单起见，该示例仅限于由一个源和两个接收传感器阵列组成的二维场景。您可以将这种方法扩展到两个以上的传感器或传感器阵列以及三维。

Beamform signals received by an array of microphones to extract a desired speech signal in a noisy environment. This Simulink® example is based on the MATLAB® example Acoustic Beamforming Using a Microphone Array for System objects.

使用Si金宝appmulink®抑制来自机雷达的接收脉冲的杂波和干扰干扰。它说明如何模拟杂波和干扰干扰以及如何使用自适应位移阶段中心阵列（ADPCA）脉冲消除器块以抑制干扰。ADPCA消除器是分阶段阵列系统工具箱™中提供的若干时空自适应处理（STAP）块之一。有关在Simulink®中建模端到端单体雷达的更多信息，请参阅端到端的单体雷达示例。金宝app有关STAP的简介，请参阅时空自适应处理示例的简介。

在Simulink®中将常规和自适应波束成形应用于由天线阵列接收的窄带信号。金宝app信号模型包括噪声和干扰。该示例基于传统和自适应波束形成器示例。

Use beamscan and minimum variance distortionless response (MVDR) techniques for direction of arrival (DOA) estimation in Simulink®. It is based on the MATLAB® example Direction of Arrival Estimation with Beamscan, MVDR, and MUSIC.