Detection of Threat Situation for UAV Collision Avoidance Based on Sliding Window Polynomial Fitting Prediction Method

The detection of air threat situation is the key to the early warning for UAV flight collision avoidance. For this reason, a detection method of air threat situation based on sliding window polynomial fitting prediction is proposed. Firstly, the sliding window polynomial fitting method is used to dynamically predict the track of the intruder. Then, on the basis of the track prediction, using the flight information of UAV and intruder, the detection and alarm for flight conflict trend between UAV and intruder is carried out in a specific flight scenario. Simulation validates the effectiveness of the proposed method and the feasibility of application in the early warning for UAV flight collision avoidance.