Development and Application of a Multi-sensor Fusion Height Measurement System
In order to address the problem of accurately calibrating the real-time altitude of unmanned aerial vehicle (UAV) pollution measurement platforms when measuring the vertical distribution of atmospheric pollutants in the air,this paper analyzes the error characteristics of different current UAV altitude measurement methods and proposes a measurement method that uses the Kalman filtering algorithm to fuse sensor data. By fusing the height data measured by GPS,barom-eter,and accelerometer sensors,the measurement accuracy and robustness of the system are improved. After actual testing,the use of this method to fuse calculated height data resulted in an error control within a range of 0.3m,which is better than the results of other existing measurement methods. Comparison results of measurements in different meteorological en-vironments show that the system has the advantages of accurate measurement data and strong resistance to meteorological interference,which can meet the real-time altitude requirements of pollution UAVs.
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