Sense And Avoid Technology For Unmanned Aircraft Vehicles

The unmanned aircraft vehicles (UAVs) have been increasingly employed in the military reconnaissance in the battlefield as well as various civil applications. The safety of the UAV needs to be guaranteed during the mission, which makes the ability to see and avoid the environmental threats an urgent issue. This dissertation is focused on the non-cooperative autonomous detection and avoidance technology for the UAV, research is mainly composed of the system solution design, the obstacles tracking, the collision avoidance path planning and the path following control. The detailed contents are presented below:1. Based on the analysis of key issues of the non-cooperative see and avoid technology for the UAV, the whole system has been divided into four sections, namely the detection platform design, the object tracking, the collision avoidance path planning and the path following control. The implementation methods have been carefully designed and verified with respect to the characteristics of each section.2. In order to adapt the nonlinear property of the obstacle tracking, the quadrature Kalman filtering (QKF) process has been deduced and the configuration of the sparse grid integration points has been studied. Besides, the maneuver and non-maneuver tracking models have been established and analyzed in the interactive multi-model (IMM) frame. Aiming at the mismatch issue of the tracking model and the actual movement of the target, the Singer model with appropriate time constant has been proposed to track different maneuvering target. What’s more, the Singer models with different parameters have been set in the IMM frame so as to track all kinds of target maneuvers, and the simulation results show that this method can effectively improve model mismatching phenomenon.3. The turn maneuver tracking has been studied. Based on the solution of the mismatch issue, the characteristics and differences of the horizontal turn maneuver and the three dimensional turn maneuver have been analyzed, and an adaptive IMM tracking algorithm has been proposed that two types of the turn maneuvers are discriminated through vertical motion, then it estimates the instantaneous turn rate to establish the tracking model to perform accurate target tracking. The simulations and data tests have demonstrated the effectiveness of the adaptive IMM tracking algorithm.4. The dynamic path planning technique of the UAV see and avoid has been studied. For that local minima problems that would appear in the UAV environment, corresponding solutions of the deadlock issue and the oscillation movement issue have been studied to improve the performance of the artificial potential field method. In addition, the obstacle model has been established and the repulsion potential field of the obstacle has been redefined to enhance the avoidance safety. The relationship between the path planning and aircraft features has been further studied, and an improved artificial potential field path planning algorithm that conforms to the physical constraints of the fixed-wing aircraft and the flight motion constraints has proposed to achieve reachable avoidance path. The efficacy of the proposed dynamic path planning algorithm for UAV has been illustrated by the simulations and data tests.5. The aerodynamic model of the fixed-wing aircraft has been derived. The state space model of the control system has been established and then decoupled into the lateral model and the longitudinal model. According to the properties of each model, two PID controllers and a robust controller have been designed, respectively. The controller is to track the aircraft speed, the pitch angle, the roll angle and the yaw angle to fulfill the avoidance path following. In the semi-physcial simulations, the path following controller has shown its feasibility by comparing the distance between the controlled path and the obstacle with the minimum safety distance of the avoidance.