Research On The Integrated Attitude Algorithm Based On MEMS In USV Cooperative Navigation

With exploring marine gradually and increasing requirements of military complexly in countries,the cooperative combat of unmanned surface vessels become a new hot spot with its low cost,complete function,simple structure,high reliability,high efficiency,wide coverage and so on in research of the surface work platform.However the technology of unmanned surface vessels cooperative combat has many problems when it is applied to practical application,the primary problem is to improve the positioning accuracy.When previous researchers study of the cooperative navigation and the positioning accuracy,they mostly focused on the whole fleet of cooperative positioning system,such as research on the collaborative navigation algorithm,the formation control,a fleet formation,path planning and other aspects.Although these methods can make the cooperative positioning system achieve better the positioning performance,positioning error caused by low navigation sensor precision will restrict the positioning accuracy of the whole cooperative navigation system Thus it is the vital for cooperative navigation system to improve the positioning accuracy of the follower of USV.In this paper,two parameters is used to calculate position of the follower of USV,the one is the heading value of MEMS inertial sensors output,the other one is the speed value of DVL output,the measuring speed precision of DVL is higher,the MEMS inertial sensor precision is low and gyro drift is larger,so the output of the heading information is the main error sources for dead reckoning.So this article focuses on improving the precision of attitude estimating for USV,then getting the exact heading value,for the purpose of increasing the location accuracy.Firstly,against the background of the integrated attitude algorithm based on MEMS in USV cooperative navigation vessels,this paper details the basic features of the integrated navigation system and the mathematical description of the MEMS sensor system,as well as introducing the conventional filtering estimation theory,ore shadowing for the research the above content provide foundation for behind study.Secondly,deducing the nonlinear error model of the integrated attitude system based on MEMS for low precision of the inertial sensors.We used respectively EKF filtering algorithm to estimate system's attitude for nonlinear systems to fuse the information of MIMU/DVL and MIMU/magnetometer.Then,in order to obtain more accurate and stable attitude measuring value,combinating with MIMU?DVL and magnetometer to realize the complementary advantages of each sensor,and focused on the model of non-linear combination system considering improve filtering algorithm to design a new kind of nonlinear filtering algorithm based on maximum likelihood criterion SRCDKF filter method,this method can improve the non-linear error better than caused the conventional kalman filter dose,when the statistical properties of system are inaccurate,it assures the effectiveness and reliability to estimate the system attitude under dynamic circumstance.Finally,combining with the characteristics of the unmanned surface vessels collaborative navigation,co-location technology are used to get a relative accurate location information of the following boat to correct its own heading error,compensating positioning error caused by heading angle error,achieving the goal of the collaborative navigation system positioning accuracy.