| 1. | Minimum variance estimator
最小方差估计量 |
| 2. | Minimum variance estimation
最小方差估计 |
| 3. | After converting multiple speckle noise to additional gaussian noise , we achieve the mmse estimate of sar image wavelet coefficient
将乘性噪声转化为近似加性高斯噪声，可以获得sar图像小波系数的最小方差估计。 |
| 4. | In this case optimally weighted ls estimate is not a linear estimate of a parameter given input and observation anymore and can not be compared with linear minimum variance estimate
在这种情况下，最优加权最小二乘估计变成关于观测和输入的非线性估计，且与线性最小方差估计不可比。 |
| 5. | Based on the linear unbiased minimum variance estimation theory , an asynchronous fusion algorithm that fused the state vector of linear system with arbitrary correlated noises is developed
摘要基于线性无偏最小方差估计理论，提出了一种任意相关杂讯线性系统非同步状态向量融合算法。 |
| 6. | Linear minimum variance estimate and optimally weighted ls estimate are often used in many fields such as signal processing , control and communications . kalman filtering is the recursive version of ihe first estimate
在信号处理、控制和通讯等技术领域，常常使用线性最小方差估计和最优加权最小二乘估计对参数作出估计。 |
| 7. | In this paper we mainly discuss the problem about minimum variance estimation for linear model and bring out the relevance and difference of performance between the two methods in order to provide theoretic foundation for choosing appropriate estimation method
本文针对这种线性(观测)模型下的最小方差估计问题进行了深入讨论，指出这两种估计性能之间的关系及差别，从而为选择恰当的估计方法提供理论依据。 |
| 8. | Then we give the necessary and sufficient condition under which the optimally weighted ls estimate is identical to thu conditional mean of the parameter given input and observation , i . e . , the optimally weighted ls estimate could be optimal nonlinear estimate in the minimum variance sense
在方差阵可逆的条件下，我们发现最优加权最小二乘估计优于线性最小方差估计，进而得到了其与最小方差估计(即条件均值估计)等价的充要条件。 |
| 9. | For a general linear model ( input matrix is deterministic ) , under a certain conditions on variance matrix invertibility , the two estimates can be identical provided that they have the same priori information on the parameter under estimation . even if the above information is unknown only for the optimally weighted ls estimate , the sufficient condition and necessary condition , under which the two estimates are identical , is derived . more significantly , we know how to design input of the linear system to make the performance of the optimally weighted ls estimation identical to that of the linear minimum variance estimation in case of being lack of prior information
在一般线性模型(即输入矩阵为确定性)下，当两种估计都利用有关被估参数的先验信息时，二者在方差阵可逆的一定条件下可达到一致；当最优加权最小二乘估计不利用此先验信息时，存在二者一致的充分条件和必要条件，进而找到一种设计输入矩阵的方法，使得在先验信息缺乏的条件下，仍可利用最优加权最小二乘估计达到与线性最小方差估计一样优越的估计性能。 |
| 10. | An on - line minimum - variance estimator was developed for thrust acceleration applied to orbit transfer using discrete - time radar measurements . the mass - flow - rate of propellant was selected as a state variant , which was estimated by employing an integral state model and ekf filter . the variation equations for measurement vector to mass - flow - rate have been established to linearize the discrete - time measurement equations . the algorithm has applied successfully to maneuver process in commanding satellite into geo - stationary orbit . the results show that the algorithm developed here can monitor and determine whether engine works well or failure precisely and quickly during orbit transfer process
飞行器轨道机动过程中,为跟踪、定位机动目标和干预机动控制过程,需要统计处理离散的雷达观测量实时估计推进发动机的推力,进而确定飞行器的瞬时轨道参数.本文所述算法是该工程问题的探讨和解决方案.文章建立了轨道机动过程中连续变质量运动模型和离散雷达量测模型,推进发动机的质量秒耗量作为表征推力加速度的一个近似常量,应用扩展卡尔曼滤波对离散的雷达测量数据进行顺序统计处理给出秒耗量的最小方差估计;文章详细地推导了线性化量测模型的变分方程和观测矩阵;仿真结果表明该算法能快速、准确地估计推进发动机的质量秒耗量和向机动目标施加的实际推力 |
