这是我师兄做的空间谱估计的内容。
随后详细讨论了传统空间谱估计方法。
Then, several ways of traditional DOA estimation are discussed in detail.
相干信号源的测向是空间谱估计的一个难题。
DOA of correlated signals is difficult question of space spectrum estimation.
对信号波达方向(doa)的估计是空间谱估计研究的主题。
The main studied topic of spatial spectrum estimation is the direction of arrival (DOA) of spatial signals.
它是建立在阵列输出信号和噪声参数联合后验概率密度基础上的空间谱估计。
It is established on the expected value of the theoretical spatial spectrum over the joint posterior density function of the array output signal and noise parameters.
空间谱估计测向是一种以多元天线阵结合现代数字信号处理为基础的新型测向技术。
Spatial spectrum estimation technique is a new direction-of-arrival estimation technique based on multielement array and modern digital signal processing theory.
基于用权微扰算法得到的协方差矩阵，提出了用单通道接收机实施空间谱估计测向。
Based on the covariance matrix obtained by the weight perturbation algorithm, we propose to use a single port receiver for spatial spectrum estimate DF.
分析了空间谱估计中多信号源方向和频率估计中通道失配和阵元互耦导致系统性能下降的机制。
The mechanism of the performance degration for space-frequency spectrum estimation due to ChannelMismatching and Sensor Coupling is analyzed.
对四阶累量混合波达方向矩阵进行特征分解，可实现有色高斯噪声背景中空域信号二维空间谱估计。
We can estimate two dimensional spatial spectra of sources in colour Guassian noises by eigen decomposing the matrix.
空间谱估计的主要目的是利用空间多传感器所构成的阵列对空间分布信号的参数和信源位置进行估计。
The main purpose of spatial spectrum estimation is to estimate the parameters and source bearing of spatial signals using spatially displaced sensor arrays.
多重信号分类(MUSIC)算法是通过对数据协方差矩阵进行本征分解获得信号空间谱估计的方法。
MUSIC (MUltiple SIgnal Characterization) is a special spectral estimation method based on the eigen decomposition of the sample covariance matrix.
利用空间谱估计理论，对外来目标信号进行超分辨测向将会成为近代电子战中必不可少的技术手段之一。
Using theory of spacial spectrum estimation to estimate Direction of Arrival (DOA) of target signals will be one of absolutely necessary technology means in future electron warfare.
基于空间谱估计的高分辨测向技术，在天线阵各通道的增益和相位未知时，其性能往往低于传统的测向技术。
The performance of the high resolution DF technique based on the spatial spectrum estimation, will be severely suffered with sensor gain and phase uncertainties.
本文首先介绍了MUSIC,ESPRIT等经典空间谱估计算法的基本原理，并进行了性能分析和比较。
The basic principle of some spatial spectrum estimation algorithm such as MUSIC, ESPRIT was described at the beginning, and their performance was analyzed and compared.
本文提出了两种处理非均匀或任意形状阵列上相干信号空间谱估计的方法阵列数据变换法和不变子空间旋转法。
The problem of bearing estimation of coherent signals impinging on an array of arbitrary geometry is studied. Two methods are developed.
空间谱估计技术，波束形成技术及零点技术是第三代移动通信标准TD-SCDMA中，智能天线的三个重要功能。
Space spectrum estimation, beamforming and nulling are important technique in smart antenna of TD-SCDMA communication standard.
信源数估计是空间谱估计中的关键技术，研究符合实际应用环境的稳健的信源数估计方法具有十分重要的现实意义。
It is very important to give out a new stable method of source number estimation to fit the real situation.
在对雷达信号的到达角估计研究中，在阵列信号处理的基础上应用空间谱估计方法是当前较为普遍而常见的处理方式。
In the researches of direction-of-arrival (DOA) of the radar signal, the spatial spectrum estimation based on the array signal process is a usual and pervasive method.
第二是对无线电信号来波方向的测量，即是要对无线电信号能量在空间的分布进行监测，这就是所谓的空间谱估计技术。
The second is the measurement of arrival direction for radio signals, which is to monitor the spatial distribution of radio energy, which is often called spatial spectrum estimation.
空间谱估计是阵列信号处理的一个重要分支，近年来在雷达、通信、声纳、地震、射线天文等科技领域取得了极为广泛的应用。
Spatial spectrum estimation is an important area in array signal processing, which is widely used in radar, communication, sonar, earthquake, chronometer and other aspects of science and technology.
以现代（非线性）谱分析理论为基础的超分辨空间谱估计技术，目的在于解决密集信号环境中的信号源高分辨和高精度测向定位问题。
The super-resolution algorithm based on modern spectrum analytical theory intends to improve DOA estimation quality in the presence of dense signals.
介绍了一种基于MUSIC算法的空间谱估计技术，对其算法原理与过程进行了详细分析，并给出了它在车载无人机测向系统中的应用。
The spatial spectrum technique based on MUSIC algorithm is mainly discussed as well as its application in the vehicle-carried direction-finding system of UAV.
在系数阵空间同样存在正交矢量谱估计方法。
Therefore, the orthogonal vector techniques can be applied to the LPEF coefficient matrix space for spectral estimation.
该方法根据空间约束和导向矢量误差约束获得相应的窄带滤波器，并利用其对Capon滤波矢量进行滤波得到谱估计。
The estimator utilizes constraints on both the subspace and the errors of steering vectors to design a narrow filter. The filter outputs the spectral estimate with the filtering vector as its input.
基于噪声（正交）子空间的频谱估计方法则具有很高的谱分辨率。
Methods based on signal-subspace, such as linear prediction, ME, etc possess better statistical stability;
基于噪声（正交）子空间的频谱估计方法则具有很高的谱分辨率。
Methods based on signal-subspace, such as linear prediction, ME, etc possess better statistical stability;
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