AMGEKF(Adaptive Modified Gain Extended Kalman Filter)自适应修正增益的扩展卡尔曼滤波
3)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。
4)MGEKF修正增益卡尔曼滤波
5)MEKF修正扩展卡尔曼滤波
1.Modified extend Kalman filter(MEKF) is simple yet very effective in accounting for the measurement of non-linearity.针对基于扩展卡尔曼滤波的融合算法存在滤波精度不高的问题,将修正扩展卡尔曼滤波算法与集中式序贯融合算法相结合,用于毫米波雷达和红外传感器目标融合跟踪。
2.Since the traditional Kalman Filter fusion has relative low filtering accuracy,Modified Extended Kalman Filter(MEKF) was used for fusion of measurements of radars for estimating the target state.传统扩展卡尔曼滤波融合算法滤波精度不高,因此先利用雷达传感器的量测,采用修正扩展卡尔曼滤波算法对目标状态进行估计,再把估计值作为红外传感器的预测值进行序贯融合。
6)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。
延伸阅读
卡尔曼滤波 见波形估计。
