To meet the requirements of a complete flight mission profile for the flying-wing Unmanned Aerial Vehicles (UAVs), autonomous and reliable attitude control under wide flying envelope plays a crucial role. How to overcome the influence of flying-wing UAVs’ insufficient longitudinal maneuverability, weak directional stability, as well as the combined effects of strong nonlinearity under wide operating conditions and external disturbances, to achieve precise and stable control, is a significant challenge. This paper focuses on the study of autonomous and reliable attitude control of flying-wing UAVs under wide flying envelope. Firstly, to overcome the effects of strong nonlinearity and model deviations of the aircraft, an Incremental Nonlinear Dynamic Inversion (INDI)-based attitude control method is designed. Combined with the dynamical characteristics of coordinated turns for vehicles, reasonable calculation of pseudo commands is achieved. Based on the proposed method, extensive simulation tests for longitudinal, lateral-direction channels and crosswind disturbances environments were carried out, to verify the effectiveness and limitations of the method. Secondly, to address the differential calculation problem in INDI, a Tracking Differentiator (TD)-based pseudo-command optimization method was designed. Finally, simulation and actual flight experiments of the attitude controller based on combining INDI and TD were conducted, and the advantages of the designed method were validated through tests in noise environments.

A three-dimensional intersection localization method for moving target using two vision-based UAVs (unmanned aerial vehicles), which did not rely on the distance information from the target point to the UAV was proposed. An interacting multiple model estimator was adopted to the localization method to solve the problem of not knowing the motion form of the moving target. A modified Sage-Husa adaptive filtering algorithm that synthesized the covariance matching technique and the positive definiteness judgment was used to improve the accuracy of localization. To assess the performance of these approaches, a set of simulations that carried out under realistic conditions were presented. Results show that the method proposed can get the accurate three-dimensional coordinates of the target. The modified Sage-Husa adaptive filtering algorithm can improve the localization accuracy significantly, with the average estimation error reduced from 27.13 m to 14.62 m under the intersection angle of 90°. The influence of the intersection angle on localization was studied in the simulation, which shows that too small intersection angle is not conductive to the improvement of localization accuracy, a larger intersection angle is good for the localization method without filtering, but the effect on the method with the modified Sage-Husa adaptive filtering algorithm is not significant.