摘要
针对车辆轨迹数据具有整体运动变化趋势的特点,提出一种顾及轨迹趋势变化的特征提取算法.首先建立趋势确定集合和待定集合,并通过计算轨迹点的趋势变化量,以确定轨迹点所在趋势集合的趋势状态;进一步,将2个趋势集合的状态进行比较判断,从而避免外界干扰因素造成的趋势干扰,获得有效的整体运动趋势;最后根据趋势特征的约束条件进行特征判断,完成趋势特征的提取.实验结果表明,该算法效率优于传统的曲线拟合算法,有效地排除了因特殊情况产生的特征干扰,简单可行、可靠性好,满足组合导航匹配的应用需要.
In view of the characteristics of the vehicle trajectory data, which has the same variation trend, this paper proposed a feature extraction algorithm in consideration of the trend changing of track. Firstly, the trend set to confirm and the trend set to pend are set up, and the state of the trend set could be determined by calculating the trend of the trajectory point. Further, the effective trend would be obtained by judging the states of the 2 trends. Finally, the constraint conditions of the feature of the trend are applied to finish the feature extraction of the trend. Experimental results show that the proposed algorithm is superior to the traditional method of curve fitting in efficiency. The interference features due to special circumstances are ruled out effectively. The proposed algorithm is not only simple and feasible, but also has high efficiency, meeting the application requirements of integrated navigation.
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2016年第8期1341-1349,共9页
Journal of Computer-Aided Design & Computer Graphics
基金
国家自然科学基金(41271450
41471336)
国家"十二五"科技支撑计划(2012BAK12B02)
关键词
轨迹特征
趋势集合
航向角
特征提取
特征干扰
vehicle track
trend sets
heading angle
extraction of features
interference features