Simulation-driven enhanced whale optimization algorithm for 3DOF unmanned aircraft model identification in C-UAS

Abstract

The escalating sophistication of unmanned aircraft in adversarial environments poses significant challenges for Counter-Unmanned Aircraft Systems (C-UAS), where rapid and precise model identification is critical. Within the constraints of the unavailability of accurate models in C-UAS, this article utilizes model identification techniques to determine reliable three-degree-of-freedom (3DOF) models with compensation terms and turn functions. The challenge of modeling an aircraft with unknown dynamics is solved. Furthermore, an improved whale optimization algorithm ATRDWOA is proposed to reduce the discrepancy between model predictions and actual behaviors in this approach. By incorporating segmented convergence factor, dynamic adaptive weights and range difference variation mechanism, a parameter estimation method for guidance commands with actual manipulated characteristics is proposed, in order to improve the prediction capability on the motion states of the aircraft. Finally, flight simulations and actual flight test confirm the validity of the proposed identification modeling scheme.