Data simulation of gravity gradient sensor and its aided navigation

In view of current domestic situation that gravity gradient data is difficult to be obtained,rectangular prism method is used to get gravity gradient data in gravity gradient forward algorithm and the data is applied in gravity gradient aided navigation.Meanwhile,in order to solve problems that most matching algorithms depend on initial position error of inertial navigation system(INS) positioning precision is not high in gravity gradient change obscure region,a new matching algorithm based on probabilistic neural network(PNN) modulated by gravity gradient variance entropy is proposed.Simulation experiment is carried out in six grids initial error,the results show that the improved algorithm is correct and effective,and matching precision is superior to the traditional probabilistic neural network matching algorithm.