Abstract: In order to solve the problems of low positioning accuracy and long time in traditional data positioning
methods，an accurate positioning method for audit information system with full coverage network data is
proposed． The nearest neighbor method is used to analyze the full coverage network data association of the audit
information system，the correlation quality function theory is introduced to transfer the multi-feature data obtained
by the sensor into the process of association decision，and the correlation measure is calculated． According to the
calculation results of the correlation measure，the target tracker is constructed through the improved KCF
algorithm，and the specific running state of the target is obtained by using the tracker． The tracking set and the
detection set of the target are obtained by using the data association algorithm． According to the data association
algorithm，the tracking set and the detection set of the target are obtained． The tracking results of weighted fusion
of three features can accurately obtain the specific position of each target data in the audit information system，
realizing the accurate positioning of the data． The simulation results show that the proposed method can quickly
and accurately obtain the specific location of the full coverage network data of the audit information system．

Key words: audit information system, full coverage, networked data, precise positioning