Distributed UWB Relative Positioning Method For UAV Swarm

In recent years,UAV swarm has attracted extensive attention in both military and civil fields because of its characteristics of no center,distributed and self-organization.The problem of positioning and measurement is an important prerequisite for the swarm to complete the formation flight and cooperative mission.The existing UAV swarm positioning measurement mostly depends on satellite navigation,but in buildings,jungles and battlefields with interference,once the satellite navigation is refused,the swarm task will not be completed.Therefore,the inter machine relative positioning technology,which only uses the mutual measurement within the swarm to determine the relative position between nodes without satellite navigation information,has become one of the important research directions in the field of UAV swarm.At present,the centralized relative positioning method has some research results,but this method can not be applied to centerless swarm.Therefore,this paper studies the distributed relative positioning problem.By means of ultra wideband(UWB)ranging,this paper decomposes the swarm distributed nnode to nnode relative positioning problem layer by layer into 1 to 1 and 1 to nsubproblems,and carries out four parts of research work around these subproblems:(1)An integrated ranging positioning algorithm framework based on distributed UWB is proposed,which realizes the overall optimization of positioning accuracy and positioning speed under the constraints of communication bandwidth and computing power,and provides a feasible solution to the problem of real-time relative positioning of UAV swarm in denial environment.Firstly,this paper models the relative positioning problem of UAV swarm,analyzes the requirements of swarm mission on positioning cycle and accuracy,and the constraints of UWB ranging and positioning in communication bandwidth,computing power,node size and so on.In view of the above challenges,the paper considers the two sub problems of ranging and positioning as a whole,includes positioning interaction in ranging communication,and uses the positioning results to optimize the ranging set,so as to improve the overall positioning performance.2)Aiming at the UWB ranging problem under the constraint of swarm communication,a distributed ranging method based on token polling is proposed,which can realize limited period distance update and dynamic self-test of communication topology.Firstly,this paper analyzes the 1-to-1 ranging element system and selects the ranging mode from the perspective of time optimization,so as to lay the foundation for the design of swarm ranging method.Then,aiming at the problem of nto nranging,a distributed ranging method based on token polling is designed,which realizes the resolution of communication conflict and the efficient management of communication bandwidth.Further,considering the token loss caused by non line of sight effect,the corresponding solution strategy is designed,and the state of swarm communication topology is detected,which provides additional decision information for swarm control.(3)Aiming at the relative positioning of swarms under the condition of partial rejection,a positioning algorithm based on least square and minimum redundant nodes is proposed to realize the comprehensive optimization of positioning time and positioning accuracy.In this paper,the UN rejected nodes are taken as anchor nodes,and the location of rejected nodes is estimated by the least square method,and the selection of the number and distribution of anchor nodes is deeply studied.It is found that when five nodes are used for positioning and meet a certain spatial distribution relationship,high-precision positioning can be realized without increasing the obvious burden of communication and calculation,which provides guidance for the application of least squares relative positioning method.(4)Aiming at the relative positioning of swarm under the condition of complete rejection,positioning algorithms based on multi-dimensional scaling and filter estimation are proposed respectively,which realizes stable and long-term location update and effective maintenance of swarm task capability.Based on the multidimensional scaling method,the relative position between nodes is obtained by solving the distance information provided by UWB in real time,which provides control input for swarm configuration maintenance and obstacle avoidance.Furthermore,the transformation of relative coordinates and absolute coordinates,as well as the swarm location and fusion for large-scale swarm are studied.According to the dynamic characteristics of UAV swarm,a positioning algorithm based on filter estimation is also designed to further improve the accuracy and robustness of swarm relative positioning.The effectiveness of the above methods is verified by numerical simulation,hardware in the loop simulation.Experiments show that the proposed method can achieve centimeter level swarm positioning accuracy under typical parameters.The research of this paper provides a full stack solution from typical tasks,partial rejection to complete rejection,which is expected to provide an effective positioning scheme for UAV swarms to perform tasks in complex scenes.