单传感器多尺度状态融合估计算法

该文在离散小波变换理论和动态多尺度系统理论的基础上，建立了一种基于单传感器的多尺度状态融合估计新算法。该方法利用离散小波变换，对Kalman滤波模型的状态方程和观测方程分别进行多尺度处理，构建多尺度Kalman滤波模型，充分利用状态估计和观测数据在不同尺度上的特征进行融合估计，获得了优于单尺度Kalman滤波及已有多尺度状态融合估计方法的处理效果。并利用Monte Carlo仿真验证该算法的有效性。 

Multi-scale Fusion and Estimation With Single Sensor

On the basis of the theories of Discrete Wavelet Transform and Dynamic Multi-scale System, we proposed a novel algorithm for multi-scale fusion and estimation using single sensor in this paper. With discrete wavelet transform, we reformulated the state equation and observation equation of Kalman filter into a multi-scale form, in order to establish a novel multi-scale Kalman filtering model. By making full use of the signal feature on the diffident scales, the estimates obtained by use of the algorithm in this paper is more accurate than the results based on single scale Kalman filter and the multi-scale fusion estimating algorithm . A set of Monte Carlo simulation is performed, and the results show that our algorithm is effective and efficient as well.