scholarly journals Cooperative Navigation Based on Bearing and Range Measurements to Different Vehicles

2020 ◽  
Vol 53 (2) ◽  
pp. 14552-14557
Author(s):  
David Santos ◽  
Pedro Batista
2014 ◽  
Vol 556-562 ◽  
pp. 3117-3123 ◽  
Author(s):  
Xing Li Huang ◽  
Li Yan Liu ◽  
Tao Tao Lv ◽  
Wen Bai Li

his paper deals with the cooperative navigation problem of multiple autonomous underwater vehicles (AUV). A novel method which does not depend on a beacon network like in long baseline positioning system is proposed. The principle of this approach is to realize the cooperative localization of AUVs by using relative range measurements between the leader and the follower vehicles by means of an extended Kalman filter. Simulation results that validate the effectiveness of this approach are presented.


2020 ◽  
Author(s):  
Clive Parini ◽  
Stuart Gregson ◽  
John McCormick ◽  
Daniël Janse van Rensburg ◽  
Thomas Eibert

Electronics ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 782
Author(s):  
Shuo Cao ◽  
Honglei Qin ◽  
Li Cong ◽  
Yingtao Huang

Position information is very important tactical information in large-scale joint military operations. Positioning with datalink time of arrival (TOA) measurements is a primary choice when a global navigation satellite system (GNSS) is not available, datalink members are randomly distributed, only estimates with measurements between navigation sources and positioning users may lead to a unsatisfactory accuracy, and positioning geometry of altitude is poor. A time division multiple address (TDMA) datalink cooperative navigation algorithm based on INS/JTIDS/BA is presented in this paper. The proposed algorithm is used to revise the errors of the inertial navigation system (INS), clock bias is calibrated via round-trip timing (RTT), and altitude is located with height filter. The TDMA datalink cooperative navigation algorithm estimate errors are stated with general navigation measurements, cooperative navigation measurements, and predicted states. Weighted horizontal geometric dilution of precision (WHDOP) of the proposed algorithm and the effect of the cooperative measurements on positioning accuracy is analyzed in theory. We simulate a joint tactical information distribution system (JTIDS) network with multiple members to evaluate the performance of the proposed algorithm. The simulation results show that compared to an extended Kalman filter (EKF) that processes TOA measurements sequentially and a TDMA datalink navigation algorithm without cooperative measurements, the TDMA datalink cooperative navigation algorithm performs better.


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