1) covariance matching estimation technology
协方差匹配估计技术
1.
Based on structure of covariance matrix from distributed sources,this paper presents a blind DOA estimation algorithm for multiple distributed sources using uniform circular array and covariance matching estimation technology.
根据分布源协方差阵结构,提出了一种利用均匀圆阵和协方差匹配估计技术的多个分布源到达方向估计算法。
2) covariance matching technique
协方差匹配技术
1.
In order to avoid the divergence and improve the real-time property of the filter, an adaptive filtering based on the covariance matching technique was proposed, which synthesized the covariance matching technique and simplified Sage-Husa filtering.
为防止滤波发散和提高系统的实时性,提出了一种基于协方差匹配技术的自适应滤波方法。
2.
The covariance matching technique to process a broadband point source and some simulations are given.
基于宽带点源入射波的阵列输出相关矩阵与窄带分布源入射波的阵列输出相关矩阵的结构相似性 ,论文提出了可利用窄带分布源角度估计技术估计宽带点源到达角的新方法 ,并给出了协方差匹配技术处理宽带点源的算法和仿真 。
3) covariance matching
协方差匹配
1.
An adaptive computation method of Kalman filter based on covariance matching technique is introduced.
研究了GPS/INS导航系统中的不确定噪声问题,给出了一种基于协方差匹配技术的自适应卡尔曼滤波算法,该法当测量噪声的协方差已知时可以自适应估计出系统噪声的协方差。
4) estimating covariance
估计协方差
1.
Aiming at the shortcoming of the estimating covariance which is obtained by given measurement variance,a new algorithm of sensor management based on time-varying measurement variance is presented.
首先,该算法根据时变的测量方差计算目标的估计协方差;其次,利用所得的估计协方差求出目标的信息增量;最后,根据信息增量最大化的原则对传感器资源进行分配。
5) covariance matrix estimation
协方差矩阵估计
1.
For the environment in which the clutter power changes slowly with distance,a novel weighting maximum likelihood estimation(WMLE) algorithm is proposed that uses the Bayes criterion to improve the approximative covariance matrix estimation for Space-Time Adaptive Processing(STAP).
针对杂波功率随距离缓变的非均匀环境,提出了一种新的基于Bayes准则的加权最大似然估计(WMLE)算法,以改善空时自适应处理(STAP)中的协方差矩阵估计。
2.
For the clutter power slowly changed environment—range-dependent nonhomogeneity,the weighting covariance matrix estimation algorithm is proposed which is based on the relative distance criterion.
针对杂波功率依距离缓变的非均匀环境,提出了基于相对距离准则的加权协方差矩阵估计算法。
6) covariance improvement estimator
协方差改进估计
1.
We give a sufficient and necessary condition for the covariance improve- ment estimator of the unknown regression coefficient and their estimable functions under the reduced model remains covariance improvement estimator in the partitioned seemingly unrelated regression model.
给出简约模型下未知回归系数及其可估函数的协方差改进估计仍是分块SUR模型下相应参数的协方差改进估计的一个充要条件。
2.
For a chass of seemingly unrelated regression system(1),when the design matrix X_1 is ill-conditioned,Wang song-gui has proposed improvement estimators _1(k)、_1(T,k) of covariance improvement estimators _1、_1(T) for covariance matrix V is known or unknown in[1].
讨论这两种有偏估计与它们的协方差改进估计β1~,β~1(T)及最小二乘估计β1∧之间的相对效率问题,并给出了相对效率的上界或下界。
补充资料：方差估计值
分子式：
CAS号：
性质：由样本测定值计算的方差S2，称为样本方差，S2是总体方差σ2的无偏估计值。因此，S2又称为方差估计值或估计方差。S和σ分别为样品测定值的标准差和样本总体呈正态分布的标准差。
CAS号：
性质：由样本测定值计算的方差S2，称为样本方差，S2是总体方差σ2的无偏估计值。因此，S2又称为方差估计值或估计方差。S和σ分别为样品测定值的标准差和样本总体呈正态分布的标准差。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条