The Prediction of Position and Orientation Parameters of Uav for Video Imaging

Abstract

ABSTRACT:The paper presents the results of the prediction for the parameters of the position and orientation of the unmanned aerial vehicle (UAV) equipped with compact digital camera. Issue focus in this paper is to achieve optimal accuracy and reliability of the georeferenced video frames on the basis of data from the navigation sensors mounted on UAV. In experiments two mathematical models were used for the process of the prediction: the polynomial model and the trigonometric model. The forecast values of position and orientation of UAV were compared with readings low cost GPS and INS sensors mounted on the unmanned Trimble UX-5 platform. Research experiment was conducted on the preview of navigation data from 23 measuring epochs. The forecast coordinate values and angles of the turnover and the actual readings of the sensor Trimble UX-5 were compared in this paper. Based on the results of the comparison it was determined that: the best results of co-ordinate comparison of an unmanned aerial vehicle received for the storage with, whereas worst for the coordinate Y on the base of both prediction models, obtained value of standard deviation for the coordinate XYZ from both prediction models does not cross over a admissible criterion 10 m for the term of the exactitudes of the position of a unmanned aircraft. The best results of the comparison of the angles of the turn of a unmanned aircraft received for the angle Pitch, whereas worst for the angles Heading and Roll on the base of both prediction models. Obtained value of standard deviation for the angles of turn HPR from both prediction models does not exceed a admissible exactitude 5⁰ only for the angle Pitch, however crosses over this value for the angles Heading and Roll.

Methods of Predicting the Heading, Pitch and Roll Angles for an Unmanned Aerial Vehicle

“…The maximum orientation error of the Heading angle has reached up to ±30 o , whereas for Pitch and Roll it was close to ±10 o . The obtained results of comparison of HPR predicted values are better than results in papers [10] and [15]. In addition, the simulated values of the HPR angles (e.g.…”

“…The obtained results of the HPR angles' prediction are acceptable and suitable for the UAV technology. The typical accuracy of measurement of the HPR angles equals to m HPR =2 o [10]. Moreover, the obtained results of accuracy of the HPR angles' prediction are less than boundary error of the UAV orientation error, i.e.…”

“…In References there are many different algorithms for solving the problem of predication of the HPR angles values. For example, in paper [10] the author proposed to prediction of HPR angles in the two mathematical functions: polynomial and trigonometric. The maximum range between the real and predicted data of the HPR angles is close to ±23 o .…”

Assessment of Velocity Accuracy of Aircraft in the Dynamic Tests Using GNSS Sensors

“…The aircraft position established on the basis of the GNSS technique is determined in accordance with ICAO recommendations using BLh(B-Latitude, L-Longitude, h-ellipsoidal height) ellipsoid coordinates [4]. In turn, the flight speed can be estimated based on the difference of: XYZ geocentric coordinates or ENU (E-Easting, N-Northing, U-Up) local coordinates whereas the HPR (H-Heading, P-Pitch, R-Roll) orientation angles are typically specified in the ENU local coordinates [5]. The determination of aircraft navigation parameters is very important for maintaining and ensuring the continuity of flight mechanics [6,7,8].…”

Determining the Elements of Exterior Orientation in Aerial Triangulation Processing Using UAV Technology

“…The unknown parameters from Equation (1) are determined using the Kalman filtering in accordance with interval recording of an observation. The UAV coordinates are used to determine the coordinates of the projection center for each image, see below [13][14]:…”