Fast Robust All-source Localization Method For Cooperative Navigation In Interference Environment

Navigation has evolved from the earliest single navigation mode of inertial navigation using inertial components or satellite navigation with the aid of wireless communication technology to the combined navigation mode of multiple navigation means participating in the navigation task.But with expanded in the field of navigation,the navigation system of navigation environment is more complex,and navigation system in a growing number of navigation platform navigation task,so use Internet technology to build up more navigation platform of the communication network collaborative navigation mode is now the most common research methods to solve the above problems.This paper mainly studies the construction of cooperative navigation system and the algorithm of cooperative navigation,which is mainly divided into the following three parts.For inertial navigation and a brief introduction to the working principle of satellite navigation,and analyzes under the single navigation error modeling,then according to the integrated navigation mode of absolute navigation for preliminary positioning navigation platform of the information,and then use the ultra-broadband technology for relative navigation information,establish more navigation communication network platform,and through the information interaction between messaging algorithm implementation platform,Finally,the physical platform of cooperative navigation system is built.A variational adaptive cooperative navigation filter is designed to solve the problem that the cooperative navigation system is interfered by external factors.Firstly,unscented Kalman filter was used to update the time of cooperative navigation.Then,combined with the measurement information obtained by UWB communication,message passing algorithm was used to realize the information interaction between platforms.Then a sliding window model is designed for the state and covariance estimates obtained by the above filtering,and then the covariance of time-varying noise in the cooperative navigation process is smoothed.Finally,the updated noise covariance matrix is fed back to the forward filtering process to improve the accuracy of navigation information in cooperative navigation.In order to solve the cooperative problem of large-scale multi-motion navigation platform,firstly,the random finite set is used to model the state and quantity measurements and attach labels to solve the unknown problem of navigation platform participating in local networking.Then,the confidence propagation algorithm based on factor graph model is used to realize fast marginalization and solve the uncertainty problem of probabilistic data association between navigation platform and quantity measurement in cooperative navigation.Then,the covariance cross method is used to deal with the fusion of two different measurements in the cooperative navigation process.Finally,the state trajectory of navigation platform in cooperative navigation system is estimated.Finally,MATLAB software simulation was used to verify the algorithm and effect of each part.The simulation data prove the feasibility and superiority of the cooperative navigation algorithm proposed in this paper,which effectively improves the robustness and stability of the multi-motion platform cooperative navigation system,reduces the communication cost of the system,improves the rapidity of the system,and enables the system to better adapt to the complex environment and successfully complete the navigation task.