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.
引文
[1]文华,黎智.多源通信网络全局信息融合方法仿真[J].计算机仿真, 2018, 35(1):188–191.
[2]陈伟强,陈军,张闯,等.基于智能粒子滤波的多传感器信息融合算法[J].计算机应用, 2016, 36(12):3358–3362.
[3]闫钧华,肖勇旗,姜惠华,等.融合区域像素显著性和时域信息的地面动目标检测及其DSP实现[J].电子设计工程, 2018,26(19):178–183.
[4]郝士林,严超,毕进.武器系统基于GPS时间同步方法研究[J].火控雷达技术, 2017, 46(3):1–5.