1) MGEKF
修正增益卡尔曼滤波
2) MGEKF
修正增益扩展卡尔曼滤波
1.
The Modified Gain EKF(MGEKF)algorithm for passive localization of maneuvering target by single station is discussed.
在建立目标机动模型与测量方程的基础上,运用修正增益扩展卡尔曼滤波(MGEKF)算法,实现对机动目标进行定位与跟踪。
2.
The paper presents a single observer passive location algorithm which is based on azimuth and elevation angle and TDOA measurement and adds the changing rates of azimuth angle,meanwhile,introduces a filtering algorithm which is good for nonlinear system,modified gain extended Kalman filter(MGEKF) algorithm.
同时引入一种对非线性系统较好的滤波算法——修正增益扩展卡尔曼滤波(MGEKF)算法,与推广卡尔曼滤波器(EKF)相比,MGEKF能更好地解决量测模型非线性问题,滤波性能更好。
3.
The modified gain EKF(MGEKF)algorithm for passive localization of maneuvering target by single station is discussed.
在建立目标机动模型与测量方程的基础上,运用修正增益扩展卡尔曼滤波(MGEKF)算法,实现对机动目标进行定位与跟踪,讨论了其定位原理与算法,计算机仿真验证了该方法的正确性与有效性。
3) AMGEKF(Adaptive Modified Gain Extended Kalman Filter)
自适应修正增益的扩展卡尔曼滤波
4) modified gain extending Kalman filter
修正增益推广卡尔曼滤波器
1.
Using modified gain extending Kalman filter, this algorithm regards the constraints of moving target warship as additional measures, output of which is zero, and adds it to the measure equation; the constraints intensity is decided by the constraints noise variance.
提出一种基于航速修正处理的单舰被动定位算法,在修正增益推广卡尔曼滤波器的基础上,该算法把运动目标舰艇的航速约束当作输出为0的增加的观测数据加入到测量方程,约束的强度由约束条件的噪声方差确定。
5) MGEKF
修正增益的扩展卡尔曼滤波
1.
By establishing maneuvering target model and measurement formula,the location of maneuvering target is practicable with the MGEKF algorithms.
在建立目标机动模型与测量方程的基础上,运用修正增益的扩展卡尔曼滤波(MGEKF)算法,实现对机动目标进行定位与跟踪。
6) time varying sampling MGEKF
时变采样间隔的修正增益推广卡尔曼滤波
补充资料：卡尔曼滤波
见波形估计。
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