【摘要】 对于带有不同观测阵、相关观测噪声和未知噪声统计的多传感器线性离散定常随机系统,利用相关方法,得到了噪声统计信息的在线辨识器。基于ARMA新息模型,提出了自校正加权观测融合Wiener滤波器,避免了求解Lyapunov和Ricca-ti方程,减少了计算负担,适于实时应用。利用动态误差系统分析(DESA)方法,严格证明了提出的自校正融合Wiener滤波器以概率1或按实现收敛于相应的最优观测融合Wiener滤波器,即具有渐近全局最优性。一个3传感器跟踪系统的仿真例子说明其有效性。更多还原

【Abstract】 For the multisensor system with different measurement matrices,correlated measurement noises and unknown noise statistics,by correlated method,the online identifiers of the noise statistics are obtained.Based on ARMA innovation model,a self-tuning weighted measurement fusion Wiener filter is presented,which avoids Lyapunov and Riccati equations,reduces the computational burden and is suitable for real time application.By dynamic error system analysis(DESA) method,it is strictly proved that the proposed self-tuning fused Wiener filter converges to the corresponding optimal fused Wiener filter with probability one or in a realization,i.e.it has asymptotic global optimality.A simulation example for a target tracking systems with 3 sensors shows its effectiveness.更多还原