Establishment And Calibration Of Target Positioning Model Applied In Large Field Space

Presently, there are mainly three airport surface surveillance techniques at home and abroad: SMR(surface movement radars), ADS-B(Automatic Dependent SurveillanceBroadcast), and MLAT(Multilateration). All these methods presented have some limitations: ADS-B positioning information from GPS global positioning system can only provide the accuracy of the position information of 30 meters, not satisfying the requirements of ground positioning accuracy that the international civil aviation organization has set. Ground position precision of MLAT can reach 10 meters, but relies on active responses or reports by monitoring. As the only means of non-cooperative surveillance, surface movement radar has the accuracy of 17 m, with problems of being sensitive to weather conditions, blind area coverage and expenses.A non-cooperative surveillance technique with high precision for airports would be a useful complement to the airport surface surveillance. This paper proposes a method based on binocular stereo vision for improving the measurement precision of moving objects on airport surface for the Advanced Surface Movement Guidance and Control Systems(A-SMGCS). the accuracy of the model applied for Surface surveillance is assessed through theoretical analysis and experimental verification.Specific contents are as follows: First of all, based on the theory of visual measurement, a calculating model is established and simplified according to parameter sensitivity. Secondly, a new calibration algorithm is researched on the basis of new calculating model and a new calibration method is put forward on the condition that it is not allowed to put targets within the view scope. The impact of the parameters of calculating model on the monitoring range is analyzed. Setting parameters to achieve the most extensive visual range in the airport environment is studied. In addition, the measurement accuracy of the calculating model is analyzed.Finally, we can come to the conclusion that surface surveillance based on binocular vision measurement is superior to the traditional surface surveillance techniques in accuracy.