摘要
本文提出一种以自适应加权融合算法为核心的信息多层融合方法,以解决以往经典算法下舰船GPS定位软件雷达跟踪信息融合度低的问题。方法首先进行信息预处理,包括坐标变换与时间对准2个方面,然后对GPS和雷达的定位信息进行关联度判断,最后利用自适应加权融合算法对关联度较高的GPS和雷达定位信息进行合成。结果表明:本方法信息融合平均标准差小于D-S证据理论与人工神经网络下2种方法的平均标准差1.238和1.106,融合程度更高。
In this study,a multi-layer information fusion method based on adaptive weighted fusion algorithm is proposed to solve the problem of low fusion degree of radar tracking information in ship GPS positioning software under the classical algorithm.Methods Firstly,information pretreatment was carried out,including coordinate transformation and time alignment.Then,the correlation degree of GPS and radar positioning information was judged.Finally,the information of GPS and radar positioning with high correlation degree was synthesized by adaptive weighted fusion algorithm.The results show that the standard deviation of information fusion in this method is less than the average standard deviation of 1.238 and1.106 in D-S evidence theory and artificial neural network,and the fusion degree is higher.
作者
曾赟
郭晓娟
ZENG Yun;GUO Xiao-juan(Yellow River Conservancy Technical Institute,School of Information Engineering,Kaifeng 475000,China)
出处
《舰船科学技术》
北大核心
2019年第8期169-171,共3页
Ship Science and Technology
