A Data Analysis Algorithm of Missing Point Association Rules for Air Target

It is important to analyze missing point phenomenon in early warning. By using data mining method, the association rules between air target missing point and status of early warning equipment can be concluded. A new mining algorithm is proposed, which firstly divided the target track into two categories, and then acquired the target air track net units with the same characters by clustering. Through matrix calculating and filtering false correlation sets, the association rules can be found. Experimental results demonstrated that this algorithm is efficient and accurate to mine the association rules among missing point events.