用于导航姿态测量的改进人工蜂群算法OA

The attitude measurement of a navigation satellite is based on the vector description of the baseline with the phase differ-ence of the satellite carrier,and then the attitude information of the carrier is calculated according to the attitude solving algorithm.In order to improve the accuracy of attitude Angle calculation with the help of an intelligent optimization algorithm,an attitude An-gle calculation algorithm based on the artificial bee colony algorithm is proposed.By introducing two basic line vectors into the pro-cess of solving the Wahba problem,a fitness function model of attitude Angle is constructed.With the help of the overall frame-work of artificial bee colony algorithm,3D-CSCM chaotic mapping is used to improve the initial ergodicity of the algorithm,and the beetle antennae search algorithm is used to improve the convergence performance of the algorithm.Finally,the attitude Angle value is searched and solved.Through comparative experiments,the static measurement error of the yaw algorithm is 0.002 446°,the pitch Angle is 0.001 654°,and the roll Angle is 0.006 808° at the baseline lengths of 105.588 1 m and 47.047 3 m,which is superior to the classical SVD algorithm and QUEST algorithm,and can meet the requirements of real-time static attitude solving.