云平台最速梯度准则的船摇数据自适应滤波快速算法

Fast adaptive filtering algorithm for ship rolling data based on the cloud platform

在海洋船舶遥感测绘领域,由于受到海风海浪等作用力的影响,船舶的动态及静态测量数据受到了来自船摇误差等多方面影响,实测数据需要经过处理才能得到更准确的数据。基于最速梯度最小二乘法对实测数据建立了可调步长递推准则,通过自适应的滤波过程,可有效滤除实测数据的船摇干扰数据。本文研究船舶遥感测量数据的船摇过滤算法模型,并利用云计算平台实现对实测数据的自适应最小二乘算法过滤,最后给出仿真结果。

In the field of marine remote sensing mapping,influenced by sea waves and other forces,the ship's dynamic and static measurement data affected by the ship swing error and other aspects,the data needs to be processed to become more accurate. Based on the least square method with the most velocity gradient,the step size of the measured data is established,and the adaptive filtering process is established,this can effectively filter the measured data of equivalent ship shaking interference data. In this paper,the ship rolling filtering algorithm model of ship remote sensing data is studied,and an adaptive least square algorithm is used to filter the measured data,at last this paper give the simulation results.