海上无人驾驶技术中的数据融合应用技术
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摘要
现有的海上无人驾驶船舶数据融合应用技术存在数据精度差、数据波动大的弊端,为了解决上述问题,提出海上无人驾驶船舶数据融合应用技术研究。AIS与雷达设备采集的船舶数据存在较大的差异,采用聚类方法与高斯-克吕格投影方法分别对数据的时间与空间进行校准,得到采集时间序列一致、表述一致的船舶数据,以此为基础,利用模糊数学算法对目标船舶的关联航迹数据进行求取,以关联航迹数据为依据采用加权融合算法对AIS与雷达数据权值进行分配,实现海上无人驾驶船舶数据的融合应用。通过性能测试得到,与现有的数据融合应用技术相比较,提出的海上无人驾驶船舶数据融合应用技术极大的提升了数据精度,降低了数据波动的幅值,说明本文方法的海上无人驾驶船舶数据融合应用技术具有更好的性能。
The existing data fusion application technology of unmanned ships at sea has the disadvantages of poor data accuracy and large data fluctuation. In order to solve the above problems, the data fusion application technology of unmanned ships at sea is proposed. There is a big difference between the ship data collected by AIS and radar equipment. Clustering method and Gauss-Kruger projection method are used to calibrate the time and space of the data respectively, and the ship data with the same time series and the same expression are obtained. Based on this, the associated track data of the target ship is obtained by using the fuzzy mathematics algorithm, and the data of the associated track is taken as the basis. The weighted fusion algorithm is used to distribute the weights of AIS and radar data to realize the data fusion application of unmanned ships at sea. Through the performance test, compared with the existing data fusion application technology, the proposed data fusion application technology for unmanned ships at sea greatly improves the data accuracy, reduces the amplitude of data fluctuation, fully demonstrates that the proposed data fusion application technology for unmanned ships at sea has better performance.
The existing data fusion application technology of unmanned ships at sea has the disadvantages of poor data accuracy and large data fluctuation. In order to solve the above problems, the data fusion application technology of unmanned ships at sea is proposed. There is a big difference between the ship data collected by AIS and radar equipment. Clustering method and Gauss-Kruger projection method are used to calibrate the time and space of the data respectively, and the ship data with the same time series and the same expression are obtained. Based on this, the associated track data of the target ship is obtained by using the fuzzy mathematics algorithm, and the data of the associated track is taken as the basis. The weighted fusion algorithm is used to distribute the weights of AIS and radar data to realize the data fusion application of unmanned ships at sea. Through the performance test, compared with the existing data fusion application technology, the proposed data fusion application technology for unmanned ships at sea greatly improves the data accuracy, reduces the amplitude of data fluctuation, fully demonstrates that the proposed data fusion application technology for unmanned ships at sea has better performance.
引文
[1]叶强.智能船舶技术和无人驾驶技术研究[J].山东工业技术,2017,12(15):106-106.
[2]朱婉莹,刘艳琴.数据融合技术在航测内业生产中的应用[J].城市地理,2018,9(2X):128-129.
[3]彭鸣.雷达、AIS数据融合应用技术研究[J].信息与电脑(理论版),2018,56(8):39-41.
[4]邓晓东,何庆,许敬伟,等.大数据网络安全态势感知中数据融合技术研究[J].网络安全技术与应用,2017,23(8):79-80.
[2]朱婉莹,刘艳琴.数据融合技术在航测内业生产中的应用[J].城市地理,2018,9(2X):128-129.
[3]彭鸣.雷达、AIS数据融合应用技术研究[J].信息与电脑(理论版),2018,56(8):39-41.
[4]邓晓东,何庆,许敬伟,等.大数据网络安全态势感知中数据融合技术研究[J].网络安全技术与应用,2017,23(8):79-80.