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.

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.

This paper describes a synthetic aperture radar system for tactical-level imagery intelligence installed on board an unmanned aerial vehicle. Selected results of its tests are provided. The system contains interchange-able S-band and Ku-band linear frequency-modulated, continuous wave radar sensors that were built within a frame of a research project named WATSAR, conducted by the Military University of Technology and WB Electronics S.A. One of several algorithms of radar image synthesis, implemented in the scope of the project, is described in this paper. The WATSAR system can create online and off-line radar images.