SUMMARY
The particle filter offers a general numerical tool to approximate the posterior density function for the state in nonlinear and non-Gaussian filtering problems. While the particle filter is fairly easy to implement and tune, its main drawback is that it is quite computer intensive, with the computational complexity increasing quickly with the state dimension. One remedy to this problem is to marginalize out thestates appearing linearly in the dynamics. The result is that one Kalman filter is associated with each particle. Filtering block has been developed with the help of which navigation data received from UAV is filtered. UAV motion with camera on board has been conducted and photos have been captured from it. Photos have been processed by OpenSurf method, with the help of which feature points has been detected,filtered and compared with previous image. Result of research shows that with help of comparing of two neighboring images we can reconstruct relief above which UAV flew.