GPS的多尺度滤波算法研究

Research on GPS Multi-Scale Filtering Algorithm

摘要:

将基于模型的GPS动态系统分析方法与基于统计特性的多尺度信号变换方法相结合,在某一尺度上给定的单传感器单模型动态系统中建立起一个新的多尺度动态模型。基于建立的多尺度模型和常规Kalman滤波,提出一个能同时对随机信号进行多尺度分解与多尺度估计的新算法,并通过Haar小波仿真试验获得了比仅利用Kalman滤波更好的估计效果,验证了算法的有效性。

Abstract:

By combining the model-based analysis for dynamic systems with multi-scale signal transformation, a new multi-scale dynamic model based on dynamic system with single model and single sensor at one given scale was proposed. By developing Kalman filtering, a new multi-scale algorithm was put forward for stochastic signal on the basis of the multi-scale dynamic model, and it could simultaneously implement decomposition and estimation for stochastic signal. The estimation obtained by use of the new algorithm with Haar wavelet were more accurate than the results based on Kalman filtering, and it showed the efficiency of the new algorithm.