CAJ | 학술논문

从矩阵论和数理统计理论的角度，阐述了联邦滤波与Gauss-Markov估计的内在联系，论证了联邦全局最优滤波与Gauss-Markov估计的统一性。推导了基于Gauss-Markov估计的联邦滤波信息融合算法，并与最小二乘估计的信息融合算法以及集中卡尔曼滤波算法在舰载组合导航系统中应用进行了对比。仿真结果表明，基于Gauss-Markov估计的联邦滤波信息融合算法与集中式卡尔曼滤波的精度相当，两者的估计精度均高于最小二乘估计，前者具有全局最优性。
종구진론화수리통계이론적각도，천술료련방려파여Gauss-Markov고계적내재련계，론증료련방전국최우려파여Gauss-Markov고계적통일성。추도료기우Gauss-Markov고계적련방려파신식융합산법，병여최소이승고계적신식융합산법이급집중잡이만려파산법재함재조합도항계통중응용진행료대비。방진결과표명，기우Gauss-Markov고계적련방려파신식융합산법여집중식잡이만려파적정도상당，량자적고계정도균고우최소이승고계，전자구유전국최우성。
From the perspective of matrix and mathematical statistics theory,internal connection of federated filter and Markov estimation is formulated. The uniformity of federated global optimal filtering and Gauss-Markov estimation is proved. Meanwhile,the fusion algorithm of federated filtering based on Gauss-Markov estimation and the fusion algorithm based on least squares estimation are taken a deduction and applied to the shipborne integrated navigation system. Simulation results show that filtering accuracy of fusion algorithm of federated filtering based on Gauss-Markov estimation is equal to those of centralized kalman filter. Their estimation accuracy are both higher than those of least squares estimation. The former possesses global optimality.