欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
针对带有色观测噪声的目标跟踪系统，分别用基于ARMA新息模型和基于Riccati方程的两种方法，在线性最小方差信息融合准则下，提出了多传感器按矩阵加权、对角阵加权和标量加权的三种信息融合穗态Kalman跟踪滤波器．仿真说明了三种加权滤波器的误差的差别不明显。但按标量加权滤波器显著地减少了计算负担，便于实时应用，且验证了两种方法所得结果相同．应注意在构造ARMA新息模型时，必须进行多项式矩阵的左素分解，才能得到正确的ARMA新息模型．
英文摘要：
For the target tracking systems with colored measurement noises, under the linear minimum variance information fusion criterion, three kinds of the multi - sensor information fusion steady - state Kalman filters weighted by matrices, diagonal matrices and scalars are obtained by two methods based on the ARMA innovation model and Riccati equation, respectively. Simulations show that the distinction between three filtering errors is not obvious, but the filter weighted by scalars reduces the computational burden and is suitable for real -time application. And it is verified that two methods yields the same result. Notice that constructing the ARMA innovation model, a left co-rime factorization to a polynomial matrix must be performed, so that the ARMA innovation model can correctly be obtained.
同期刊论文项目
同项目期刊论文
期刊信息
位置：