In this work, in order to achieve increased positioning accuracy, a particle filter based integrated navigation system is designed for a rotary wings unmanned aerial vehicle (UAV). As the navigation problem has highly nonlinear characteristics on the system and measurement models, the designed algorithm which is based on particle filter works more effectively with respect to Kalman filter-based algorithms which have strict linearity assumptions. In order to verify the proposed algorithm, firstly the designed navigation system is tested with a flight scenario planned in an only simulation environment. After that, the designed algorithm is tested with the data acquired on a real rotary wings system in the laboratory for a different number of particles separately and it has been shown to produce satisfactory results. In this study, an integrated navigation solution having high accuracy and reliability was calculated for a quadrotor having six degrees of freedom.