1) Array shape estimation
阵形估计
1.
Towed array shape estimation using adaptive Kalman filters;
拖曳阵阵形估计的自适应Kalman滤波算法
2.
The principle of array shape estimation based on time delay estimation is analyzed, which is a robust method of high precision, compared to direct measurement based on sensors and match-field inversion approaches.
阵形估计是水听器阵列应用中的关键问题,基于时延估计的阵形估计方法比基于传感器测量和基于匹配场处理的方法具有更强的适应性和更高的精度。
2) matrix estimation
矩阵估计
1.
Based on generalized least square (GLS) model, a dynamic origindestination (OD) matrix estimation algorithm with sliding window is established.
基于广义最小二乘模型建立了一种带滑动窗的动态起点 迄点(OD)矩阵估计算法,可通过对路段交通量和行程时间的检测来估计时变的OD数据。
3) Matrix of estimator
估计矩阵
4) OD matrix estimation
OD矩阵估计
1.
OD matrix estimation model based on the second order statistics of road flow was given based on the traditional OD matrix estimation model.
在构建OD矩阵模型时,充分考虑路网中一定连续期内各路段流量的二阶统计量和出行者路径选择的随机性,提出了一种基于路段流量二阶统计量的OD矩阵估计模型,解决了观测路段的相关性和OD矩阵估计求解的不确定性问题。
5) scatter estimator
散布阵估计
6) variance matrix estimation
方差阵估计
补充资料：随形阵列动画教程
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