基于自适应Kalman滤波的二维有噪子带信号恢复

2-D noisy subband signal reconstruction based on adaptive Kalman filtering

基于子带信号的多通道表示(multichannel representation)和输入信号的动态特征,本文尝试推出了一种多分辨率状态空间模型,它与带相加子带噪声的滤波器组(Filter Bank)系统是等价的,于是使有噪子带信号的恢复可表述为相应多分辨率状态空间模型的最优状态估计问题。进一步又利用信号的向量动态模型,发展了适于二维Kalman滤波的二维多分辨率状态空间模型。根据信号行为的分布,目标平面(object plane) 可分割为不同的区域并用不同的向量动态模型来表征信号的非平稳分布。计算机数字仿真结果进一步证实了本文所提出的二维多分辨率Kalman滤波器性能的优越性。

The multichannel representation of subband signal is combined with the dynamical model of input signal to drive the multirate state-space model for filter bank system with additive noises. Thus the signal reconstruction problem in subband system can be formulated as the process of optimal state estimation in the equivalent multirate state-space model. Incorporated with the vector dynamical model , a 2-D multirate state-space model suitable for 2-D Kalman filtering is developed. The performance of the proposed 2-D multirate Kalman filter can be further improved through adaptive segmentation of the object plane. Finally, computer simulations with the proposed 2-D multirate Kalman filter give favorable results.