单传感器多尺度状态融合估计算法

Multi-scale Fusion and Estimation With Single Sensor

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。

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 no- vel multi-scale Kalman filtering model. By making full use of the signal feature on the diffident scales, the estimates ob-tained 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 algo-rithm is effective and efficient as well.