| In modern warfare,rapid and accurate positioning and navigation ability plays an important role in the maneuverability of agents and the cooperative combat ability of the whole multi-agent system.In the open mission environment without interference,the positioning and Navigation System using the Global Navigation Satellite System(GNSS)as the agent is currently the best solution.However,when the agent is in the area of electromagnetic interference,its GNSS receiving terminal is easy to be interfered by enemy spoofing signals,so as to output wrong positioning and navigation information.This paper mainly studies the cooperative positioning and navigation problem of multiagent system under the spoofing interference of GNSS.The specific work is summarized as follows:1)Due to the strong concealment of GNSS spoofing,in the absence of effective spoofing detection algorithm,it is usually difficult for agents to find that their positioning and navigation information deviates greatly due to spoofing,which leads to the failure of the cooperative combat task of multi-agent system.To solve this problem,this paper proposes a deception detection algorithm based on trust evaluation,which determines whether the GNSS output positioning and navigation information is trustworthy through the real-time output information of inertial navigation/odometry and the trust mechanism,so as to realize the detection of GNSS deception interference,and has a good effect on the elimination of misjudgment.The effectiveness of the proposed algorithm is verified by simulation.2)For the spoofing interference of the GNSS receiving terminal of the agent in the electromagnetic interference region,this paper further studies the dynamic cooperative location problem of multi-agent system based on spoofing detection algorithm.Firstly,the minimum relative distance measurement times required for dynamic cooperative positioning are deduced theoretically.Then,a dynamic cooperative localization algorithm based on weighted semidefinite programming is proposed to achieve accurate localization of target agents.Finally,considering the influence of environmental noise,maximum likelihood estimation is introduced in this paper to make the dynamic cooperative positioning algorithm have stronger anti-interference ability.Simulation results show that the proposed algorithm has high positioning accuracy and anti-interference.3)Based on the dynamic cooperative positioning algorithm,the dead calculation system can ensure that the agent has a high precision positioning and navigation ability in a short time,but there is still the risk of error divergence during the long run.To solve this problem,a collaborative navigation algorithm based on optimal weight allocation is proposed in this paper.The extended Kalman filter and optimal weight allocation are used to integrate dead reckoning information and relative distance measurement information,and the error divergence of dead reckoning system is suppressed.At the same time,the unobservable path to be avoided is obtained according to observability analysis theory.Simulation results show that the proposed algorithm has the ability of continuous high precision positioning and navigation.4)In this paper,a semi-physical verification platform composed of unmanned vehicle,motion capture system and optical camera is built.During the experiment,the precise position of the beacon unmanned vehicle is obtained by the motion capture system,and the relative distance of the unmanned workshop is measured by the optical camera.The dynamic cooperative positioning algorithm and cooperative navigation algorithm proposed in this paper are used to calculate the position of the target unmanned vehicle in real time.The experimental results verify the correctness and superiority of the algorithm. |
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