Accuracy Improvement in GPS 3-D Localization of a Reference Object as Calibrator on Dynamic Platform
Recently, unmanned aerial vehicle (UAV)-borne radar (radio detection and ranging) calibration system has been found to be promising in replacing the conventional balloon-based calibration system which incurs challenges of deciding the reference location. However, in the UAV-borne calibration system major challenges arise due to the inherent vibration of the drone and its movement due to wind during the flight. Therefore, estimation of such vibrational noise to compensate such effects is crucial to improve the localization accuracy in weather radar calibration. The available global postioning system (GPS) positioning systems are incapable of capturing such positional movements of the UAV up to the submillimeter level. Available filtering algorithms can estimate such UAV vibration using an inertial measurement unit (IMU) but does not provide a reference location of the calibrator on the UAV unless GPS satellite data is used. In this work, a complete system is proposed that estimates the positional displacement of UAV from the GPS coordinates and provides a reference position with 0.604-mm spatial resolution utilizing IMU data. The proposed system is cost-effective as it utilizes low-cost components like Raspberry Pi, NEO 6M GPS receiver, and MPU 6050 IMU sensor. The total weight of the complete system is 158 g without battery, and dimension is $14\times 10.5\times 4.0$ cm, which is UAV payload friendly. Experimental results are presented to validate the research work with static and controlled vibration in the laboratory as well as outdoor environment during UAV flight. Effectiveness of the filtering mechanism in estimating the vibration and reducing its effect during localization of UAV-aided radar calibrator on flight is also presented.