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Author(s): |
Liang-liang Ma, School of Mathematics and Computer Science, Northwest University for Nationalities, Lanzhou 730030, China
Fu-peng Tian, School of Mathematics and Computer Science, Northwest University for Nationalities, Lanzhou 730030, China |
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Abstract: |
The steps of data fusion for multi-sensor can be divided into data preprocessing, track correlation, and tack fusion, etc. At first, conversion of units for data has been done in this paper. Then the data has been classified by the radar number, radar type, and track height, with the methods of systematic cluster analysis, trajectory which measured by each radar has been extracted, where longitude and latitude, time, velocity are the variables. Using the time slice technology of clustering, and using the outsider push data alignment algorithm of time normalization based on the information multi-sensor data, temporal registration has been done and extracted trajectories for seven objectives; VAR model has been established based on the data which observed by radar, and judged the observation precision by virtue of goodness of fitting, AIC and SC criterion of results of model test, derived the observation precision of each radar. On this basis, trajectory of observation with larger error drew closer to the trajectory with smaller error in order to eliminate the relative deviation of the radar. After error correction for radar, a trajectory of the same goal observed by radar has been fused and relative data has also been integrated. VAR model has been established with the variables of the precision, latitude and time. Software of Matlab7.0 has been used to draw the track of the goal in the future ten minutes after the model passed the model test.
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