Fast Collision Detection for Small Unmanned Aircraft Systems in Urban Airspace

With the dramatic development of small unmanned aircraft systems (sUAS), how to ensure sUAS safety operation has been a growing concern. This article proposes fast probabilistic collision detection method for based on probability density function approximations. Firstly, cylindrical zones and obstacles are established by geometrical methods simplifying modeling, instantaneous is expressed triple integral. Secondly, rapid estimation algorithm derived probability, then predicted in can be obtained maximum probabilities during encounter. Randomized tests indicate that average computation time proposed less than 0.001s, Mean Absolute Error (MAE) 0.01 Root Squared (RMSE) 0.02. Finally, numerical simulations carried out analyze influence parameters, including crossing angle, separation at closest point approach (CPA), CPA, probabilities. The optimal also discussed different types encounters. this provide support real-time avoidance definition dynamic bounds sUAS.