Sensor Data Acquisition And Processing Of Unmanned Aerial Vehicle

The autonomous navigation of small unmanned helicopter has became one of the mostpopular research topics in world today and it has broad application prospects in the civilianand even military fields. Small unmanned helicopter system is mainly composed of aircraft,power system, sensor system, control system, and other electronic devices such as laserscanners, digital cameras. As one of the most important parts, the sensor system which is thesense organ of UAV provides information such as position, velocity and attitude for the UAVnavigation. The accuracy of these information data would have a significant influence on theautonomous navigation. This paper will do further research and improvement in the sensordata acquisition and processing on the basis of the existing research results of the laboratory.This paper first introduces the types, performance parameters, communication mode anddata acquisition process of the sensors. After that, the electromagnetic interference problem ofthe sensors and the height data precision problem are being analyzed and processed. Theelectromagnetic interference problem is caused by gasoline engine spark plug. As a result ofthe existence of electromagnetic interference, it makes the sensor data are prone to theinstantaneous jump, which seriously affects the performance of autonomous navigation ofunmanned aerial vehicle. This paper first analyzes the phenomenon of electromagneticinterference, and finds out the interference source, interference transmission path andsensitive equipment through the experiments. Then some electromagnetic interferencesuppression measures such as sensitive equipment isolation, communication improvement,shielding and grounding are being taken to effectively solve the problem of the sensorelectromagnetic interference. While dealing with the height data precision problem caused bysensor noise, this paper first introduces the kalman filter algorithm and its application inunmanned aerial vehicle navigation system. Then it uses the kalman filter algorithm toprocess the height data acquired by BMP085and SCP1000barometers. With high precisiondifferential GPS as the height measurement standard, the kalman filter parameters areadjusted to reduce the barometer height data error against the height standard. Finally, the SCP1000barometer which has smaller error is selected as the sensor for height measurement.With the use of the kalman filter algorithm, the accuracy of height measurement has beenimproved.Sensor electromagnetic interference suppression and kalman filter applied in height dataprocessing is the main content of this paper. Through flight test, it shows that the measurestaken to restrain interference effectively solve the problem of sensor data jump and theapplication of kalman filter also improves the accuracy of height measurement.