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Open access

Michał Łabowski, Piotr Kaniewski, Piotr Serafin and Bronisław Wajszczyk

Abstract

Synthetic aperture radars (SAR) allow to obtain high resolution terrain images comparable with the resolution of optical methods. Radar imaging is independent on the weather conditions and the daylight. The process of analysis of the SAR images consists primarily of identifying of interesting objects. The ability to determine their geographical coordinates can increase usability of the solution from a user point of view. The paper presents a georeferencing method of the radar terrain images. The presented images were obtained from the SAR system installed on board an Unmanned Aerial Vehicle (UAV). The system was developed within a project under acronym WATSAR realized by the Military University of Technology and WB Electronics S.A. The source of the navigation data was an INS/GNSS system integrated by the Kalman filter with a feed-backward correction loop. The paper presents the terrain images obtained during flight tests and results of selected objects georeferencing with an assessment of the accuracy of the method.

Open access

Stanisław Konatowski, Piotr Kaniewski and Jan Matuszewski

Abstract

Several types of nonlinear filters (EKF – extended Kalman filter, UKF – unscented Kalman filter, PF – particle filter) are widely used for location estimation and their algorithms are described in this paper. In the article filtering accuracy for non-linear form of measurement equation is presented. The results of complex simulations that compare the quality of estimation of analyzed non-linear filters for complex non-linearities of state vector are presented. The moves of maneuvering object are described in two-dimensional Cartesian coordinates and the measurements are described in the polar coordinate system. The object dynamics is characterized by acceleration described by the univariate non-stationary growth model (UNGM) function. The filtering accuracy was evaluated not only by the root-mean-square errors (RMSE) but also by statistical testing of innovations through the expected value test, the whiteness test and the WSSR (weighted sum squared residual) test as well. The comparison of filtering quality was done in the MATLAB environment. The presented results provide a basis for designing more accurate algorithms for object location estimation.

Open access

Piotr Kaniewski, Rafał Gil and Stanisław Konatowski

Abstract

Processing of signals in Global Positioning System (GPS) receivers includes numerous signal and data operations leading to calculation of coordinates and velocities of satellites in global Earth-Centered Earth-Fixed (ECEF) frame of reference as well as pseudoranges and delta-ranges between the user and all the tracked GPS satellites. Further processing of these data consists in estimation of the user’s position, velocity and time (PVT) and nowadays it is usually realized by means of an Extended Kalman Filters (EKF). The choice of measuring data processed by the Kalman filter significantly influences the accuracy of navigation solution. In simpler GPS receivers, the estimation of user’s position and velocity is based on pseudoranges only, whereas in more advanced ones delta-ranges are also applied. The paper describes both possible solutions and compares the accuracy of estimation of the user’s position and velocity in both cases. The comparison is based on simulation results, which are included in the paper.

Open access

Michał Łabowski, Piotr Kaniewski and Stanisław Konatowski

Abstract

The paper presents a method of calculation of position deviations from a theoretical, nominally rectilinear trajectory for a SAR imaging system installed on board of UAV. The UAV on-board system consists of a radar sensor, an antenna system, a SAR processor and a navigation system. The main task of the navigation part is to determine the vector of differences between the theoretical and the measured trajectories of UAV center of gravity. The paper includes chosen results of experiments obtained during ground and flight tests.

Open access

Piotr Kaniewski, Rafał Gil and Stanisław Konatowski

Abstract

The paper presents methods of on-line and off-line estimation of UAV position on the basis of measurements from its integrated navigation system. The navigation system installed on board UAV contains an INS and a GNSS receiver. The UAV position, as well as its velocity and orientation are estimated with the use of smoothing algorithms. For off-line estimation, a fixed-interval smoothing algorithm has been applied. On-line estimation has been accomplished with the use of a fixed-lag smoothing algorithm. The paper includes chosen results of simulations demonstrating improvements of accuracy of UAV position estimation with the use of smoothing algorithms in comparison with the use of a Kalman filter.