摘要
采用卫星导航对海上航行的船舶进行速度测量是目前最广泛应用的方法,但是卫星导航接收机由于受外界偶然因素的影响,其显示的速度往往包含噪声,且属于随机的高斯白噪声。针对此问题,提出一种基于卡尔曼滤波理论的计算模型,只考虑上一个时刻和当前时刻的关系,大大地减少数据冗余;应用迭代的方法来处理卡尔曼滤波,以更好地简化计算的过程,并根据深圳某航海公司的实际数据对此计算模型进行仿真验证。实验结果表明,对于数据跳跃十分大且明显的噪声数据,经过滤波后,这些数据变得更加平滑和准确。
Satellite navigation is the method widely used to measure the speed of ships sailing on the sea.However,due to the influence of external accidental factors,the speed displayed by satellite navigation receiver often contains noise which belongs to random Gaussian white noise.To solve this problem,this paper proposes a calculation model based on Kalman filter theory concerning the relationship between the previous time and the current time,which greatly reduces the data redundancy.The iterative method is used to deal with the Kalman filter which can better simplify the calculation process.The calculation model is verified through the simulation based on the actual data of a navigation company in Shenzhen.The experimental result shows that:for those with very large jump after being filtered,these data become smoother and more accurate.
作者
岳崇伦
曾苑
郭云开
YUE Chonglun;ZENG Yuan;GUO Yunkai(Guangzhou City Construction College,Guangzhou 510900, China;Institute of Remote Sensing Applications, Changsha University of Technology, Changsha 410076, China)
出处
《测绘工程》
CSCD
2021年第2期60-64,71,共6页
Engineering of Surveying and Mapping
基金
国家自然科学基金资助项目(41671498,41471421)
广东省品牌专业建设项目(2016gzpp016)。
关键词
卫星导航
噪声
精度
卡尔曼滤波
satellite navigation
noise
accuracy
Kalman filter
