1) debiased converted measurements
去偏转换测量值
1.
The error covarinace of debiased converted measurements based on target s ture position is given,and the error covariance of debiased converted measurements based on measurements is also obtained.
在三维空间中推导了转换测量卡尔曼滤波算法 ,得到了在目标真实位置已知的条件下去偏转换测量值误差方差的表达式及在测量值已知条件下去偏转换测量值方差的表达式 ,并给出了在机动目标跟踪中 ,预测值与量测值的选择准则。
2.
The error covariance of debiased converted measurements based on target′s true position is obtained, and the error covariance of debiased converted measurements based on measurements is given too.
在三维空间中推导了转换坐标卡尔曼滤波算法，得到了在目标真实位置已知的条件下去偏转换测量值误差方差的表达式及在测量值已知条件下去偏转换测量值误差方差的表达式，用此算法进行了雷达目标跟踪仿真，取得了较好的跟踪效果。
3) converted measurements
转换测量值
1.
The error covariance of debiased converted measurements based on target′s true position is obtained, and the error covariance of debiased converted measurements based on measurements is given too.
在三维空间中推导了转换坐标卡尔曼滤波算法，得到了在目标真实位置已知的条件下去偏转换测量值误差方差的表达式及在测量值已知条件下去偏转换测量值误差方差的表达式，用此算法进行了雷达目标跟踪仿真，取得了较好的跟踪效果。
4) Second-order Debiased Converted Measurement Kalman Filter(SCMKF)
二阶去偏转换测量卡尔曼滤波(SCMKF)
5) converted measurement Kalman filter with debiasing
去偏转换测量卡尔曼滤波
1.
In this paper the interacting multiple models algorithm and the converted measurement Kalman filter with debiasing are combined to realize the maneuvering target tracking with the non linear measuring equations.
针对非线性测量下的机动目标跟踪问题 ,本文基于交互多模型算法 ( IMM) ,采用去偏转换测量卡尔曼滤波 ( CMKF- D)的方法 ,把在极坐标系下得到的测量值转换到直角坐标系中 ,用统计的方法求出转换测量值的误差均值和方差 ,将转换测量值去偏后再进行卡尔曼滤波。
2.
Based on the converted measurement Kalman filter with debiasing algorithm, the error mean and the error covariance are computed with statistical method after the polar measurements are transformed to Cartesian.
针对极坐标观测条件下的目标跟踪 ,本文基于去偏转换测量卡尔曼滤波算法 (CMKF D) ,提出了一种建立跟踪初始估计的方法 :目标初始状态由前两点观测值估计 ,初始估计误差协方差由状态方程和CMKF D中观测误差协方差计算得到。
3.
Based on the algorithm of the Converted Measurement Kalman Filter with Debiasing (CMKF-D), the error mean and error coviarance can be computed with statistical method after the polar measurements are transformed to Cartessian.
针对非线性观测的目标跟踪问题 ,本文在极坐标观测方程条件下 ,基于去偏转换测量卡尔曼滤波算法 (CMKF D) ,计算观测值转换到直角坐标系后的观测误差均值和方差。
6) CMKF-D
去偏一致转换量测卡尔曼滤波
1.
The three-dimensional CMKF-D with only position measurements is extended to solve the radar target tracking problem with Doppler measurements, where the errors between range and Doppler measurements are correlated.
将仅仅考虑位置量测的三维去偏一致转换量测卡尔曼滤波算法进行推广,以解决包含多普勒量测且斜距和多普勒的量测误差相关的雷达目标跟踪问题。
2.
The two-dimensional CMKF-D with only position measurements is extended to solve the radar target tracking problem with Doppler measurements, where the errors between range and Doppler measurements are correlated.
将仅仅考虑位置量测的二维去偏一致转换量测卡尔曼滤波算法进行推广,以解决包含多普勒量测且斜距误差和多普勒误差相关的雷达目标跟踪问题。
补充资料：黑度换值P
分子式：
CAS号：
性质：又称凯撒换值(Kaiser transformation)或专用换值黑度。乳剂特性曲线中用来代替黑度S的数值。其定义为：P=kS+(1-k)W；式中，W为换值黑度，k为换值常数，其数值与波长有关。当k=0时，P=W；k=l时，P=S；k=0.5时，上式可简化为：非记录式的测微光度计上装有黑度换值P的标尺，通称“P”标尺。
CAS号：
性质：又称凯撒换值(Kaiser transformation)或专用换值黑度。乳剂特性曲线中用来代替黑度S的数值。其定义为：P=kS+(1-k)W；式中，W为换值黑度，k为换值常数，其数值与波长有关。当k=0时，P=W；k=l时，P=S；k=0.5时，上式可简化为：非记录式的测微光度计上装有黑度换值P的标尺，通称“P”标尺。
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