基于Apriori关联规则算法提高雷达测速精度研究

Research on Improving Velocity Measurement Accuracy of Radar Based on Apriori Association Rule Algorithm

在利用初速雷达测试弹丸炮口初速的试验中,如何选择雷达的布站地点一直依靠的是参试人员的经验,始终没有一个科学准确的方法。为了解决这一难题,选择采用Apriori关联规则算法,从大量的历史试验数据中挖掘出测试的初速数据精度很高时对应的雷达布站地点。将雷达的布站地点作为关联规则的左规则、测速精度作为关联规则的右规则,利用Apriori算法就能挖掘出满足最小支持度阈值和最小置信度阈值的强规则,为确定雷达布站地点提供重要依据。通过测试数据进行验证,实验结果表明,根据挖掘出的强规则进行雷达布站,测试出的弹丸初速精度明显提升,表明该方法有效提升了初速雷达的测速精度。

When muzzle velocity radars are used for measuring the muzzle velocities of projectiles,how to choose the location of the radar station always depends on the experience of test personnel,and there is no scientific and accurate method.In order to solve this problem,the Apriori association rule algorithm is used to mine a large number of historical test data for the best location of the radar location.Taking the location of radar stations as the left rule of the association rules and the accuracy of velocity measurement as the right rule,the strong rules meeting the minimum support threshold and minimum confidence threshold can be mined by using the Apriori algorithm,which provides an important basis for determining the location of radar stations.Experimental results show that the muzzle velocity accuracy of the projectile is significantly improved when the location of the radar station is deci-ded according to the strong rules,which shows that the method can effectively improve the velocity measurement accuracy of muzzle velocity radars.