This dissertation deals with attitude estimation of multicopters. Mainly the use of multicopter dynamic model in order to gain accuracy is investigated. It shows that the usage of multicopter dynamic model brings advantage contrary to other known algorithms for attitude estimation such as GPS/INS or complementary filter. Besides others one goal is to study the possibilities to estimate the parameters of dynamic model on-line. Further the influence of wind speed to estimation accuracy is also investigated. The algorithms are based on a nonlinear Kalman filter. The use of dynamic model of multicopters reveals the possibility of estimating attitude with bounded error even without periodic measurement of absolute position. One of the results of the dissertation is a new algorithm which does not require information about the thrust of multicopter propellers.