Target Tracking Algorithm for Underwater Acoustic Sensor Networks under DoS Attack
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摘要: 考虑水下拒绝服务(DoS)攻击和声线分层效应的影响, 研究了基于水声传感器网络(UASN)的目标追踪问题。首先考虑由水下传感器、水面浮标和水下目标组成的UASN架构。基于此, 构造了水下目标运动模型和水下Dos攻击模型, 提出了一种改进的一致性无迹卡尔曼滤波(UKF)水下目标追踪算法。进一步, 证明了追踪算法的收敛性, 推导了算法的克拉美罗下界。仿真和实验结果表明, 文中算法可以在水下环境有效进行目标追踪, 基于一致性UKF的算法提高了跟踪精度。Abstract: By considering the effect of underwater denial of service(DoS) attack and sound line stratification, the problem of target tracking based on an underwater acoustic sensor network(UASN) was studied in this paper. Firstly, a UASN architecture consisting of underwater sensors, surface buoys, and underwater targets was developed. Then, the underwater target movement model and the underwater DoS attack model were constructed, and an improved consensus-based unscented Kalman filter(UKF) underwater target tracking algorithm was proposed. Finally, the Cramer-Rao lower bound of the algorithm was derived, and the effectiveness of the algorithm was proved. Simulation and experiments show that the proposed algorithm can track the target effectively in an underwater environment, and the consensus-based UKF algorithm improves tracking accuracy.
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图 4 基于一致性UKF的水下目标追踪算法
Figure 4. Underwater target tracking algorithm based on consistent UKF
表 1 文中方法与已有研究的对比
Table 1. Comparison of the proposed method and the other existing literatures’
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表 2 仿真参数列表
Table 2. Parameters of simulation
名称 数值 初始位置 [0 65 −50 5 5 0] 实验水域/m3 200×200×100 攻击参数 {1,0,1,1,1,0,0,0,1,0,1,0} 频率/Hz 21 000~27 000 通信速率/(bit/s) 300 循环次数 90
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