Research On Squad Positioning System Based On The Fusion Of MESH Network And Inertial Navigation

Pedestrian inertial positioning technology is a self-positioning technology based on micro inertial measurement unit(MIMU),which can complete the navigation and positioning of pedestrians without relying on external navigation source or auxiliary calibration signal.The accuracy of pedestrian inertial positioning technology is greatly influenced by the inertial sensor utilized in the MIMU,and the low precision inertial devices will lead to low positioning accuracy.The cost of inertial sensors vary greatly with different process levels.The fabrication cost and maintenance cost of high-precision sensors are much higher than those of low-precision sensors,which makes high-precision sensors unsuitable for mass use in pedestrian inertial positioning.Therefore,it is necessary to study the technical methods to improve the accuracy of positioning system based on low-cost inertial sensors.The navigation and positioning is usually based on the team in the case of underground operation,fire rescue,soldier operation and so on.In practical applications,the positioning accuracy of the team as a whole is very important.The pedestrian team inertial navigation positioning system can avoid using high-precision sensors for all members and reduce the overall hardware cost.At the same time,the position information of multiple members is comprehensively considered to obtain the optimal results of team position.In conclusion,this thesis proposes an inertial navigation positioning system combining high and low precision MIMUs for pedestrian teams.The data transimission among members is carried out using mesh network,which can suppress the rapid divergence of positioning errors of low-precision MIMUs and optimize the overall positioning results of the team.The main research contents are as follows:(1)The mesh network was used to construct the ad hoc network of the pedestrian team inertial navigation positioning system.A ranging model based on the received signal strength indication(RSSI)ranging principle was established to measure the relative distance between the high-precision and low-precision members was measured by using RSSI ranging principle among the members.(2)The mathematical model of pedestrian group positioning was deduced and built.The extended Kalman filter pedestrian group positioning algorithm based on relative distance information and the group member heading constraint algorithm based on pedestrian state detection were established.The feasibility of the algorithms was verified by simulation analysis.(3)The platform of pedestrian team inertial positioning system was built using high-precision MIMU and mesh ad hoc network module.Experiments were carried out to verify the heading constraint algorithm and the pedestrian team positioning algorithm.The results showed that when △ = 5 m,the track recovery degree of three low precision positioning team members walking 30 minutes under the team positioning was improved by 49.19%,46.54% and 48.05% respectively compared with pure ins positioning,which proved that the pedestrian team ins positioning can effectively improve the overall positioning accuracy of the team.