Research On UAV Integrated Navigation And Multi-UAV Cooperative Localization

With the development of microelectronics technology rotary-wing UAVs are performing complex and delicate tasks in military and civil fields with their excellent control performance,extreme adaptability to complex environments and excellent network detection performance.And the accuracy and robustness of positioning will directly determine the completion of UAV missions,so this paper focuses on the single UAV navigation under the combination of satellite/inertial sensors and the cooperative positioning of multiple UAVs under the introduction of node ranging conditions,so as to improve the positioning accuracy from single to multiple UAVs,and the main research contents of this paper are as follows:(1)Improved cubature kalman filtering algorithm.To address the nonlinear problem in the combined navigation system and the complex and variable noise in the UAV mission environment,we design a loosely coupled satellite/inertial combined navigation framework and propose an adaptive fifth-order cubature kalman filtering algorithm,which can achieve more accurate inertial/satellite data fusion and enhance the adaptability of the combined navigation system to changes in satellite positioning noise.The simulation results show that the improved cubature kalman filtering algorithm has higher computational accuracy and noise adaptation capability than the cubature kalman filtering,unscented kalman filtering,and fifth-order cubature kalman filtering algorithms.(2)Fifth-order cubature kalman filter-based initial alignment method for static bases.For the initialization of inertial navigation system error misalignment angle,the static base initial alignment method based on the fifth-order cubature kalman filter algorithm is proposed,and the state transfer equation and observation equation are designed based on the damped large misalignment angle error model and satellite observation data,which can achieve faster and more accurate misalignment angle error convergence.The simulation results show that the static base alignment method proposed in this paper has faster convergence speed and accuracy for large misalignment yaw angle than other algorithms.(3)Cooperative localization of multi-UAVs based on bilief propagation.For the problem that the positioning accuracy of different UAVs in a multi-UAV system varies greatly,we propose a cooperative localization method based on the belief propagation algorithm by adding mutual ranging information between UAV nodes and combining with the factor graph model;we propose a linearization method based on sampling for Gaussian belief propagation for the nonlinear problem of Euclidean distance ranging,and optimize the positioning accuracy of each node through the belief propagation method.The information finally achieves the uniformity of localization accuracy of all nodes.The simulation experiments show that the proposed algorithm can effectively improve the overall positioning accuracy.(4)Experimental results and analysis.The sensor calibration was completed using a quadrotor UAV and a combined navigation development board,and the inertial and satellite navigation data were collected for algorithm verification,which proved the effectiveness of the fifth-order adaptive cubature kalman filter algorithm proposed in this paper;the node distance and position data were collected by the UWB ranging module and GPS module,and the cooperative localization algorithm based on belief propagation was verified,which proved that the algorithm proposed in this paper can effectively achieve positioning error convergence.