模糊推理下多模型融合的异步测距定位算法

Multi-model fusion clock asynchronous range location algorithm based on fuzzy reasoning

针对水下节点随着洋流运动具有移动性特性,导致现有水下测距定位算法存在定位精度低、抗干扰能力差等问题.对此,提出一种模糊推理下多模型融合的异步定位算法.首先采用深海拉格朗日洋流模型描述水下节点运动规律,模拟节点运动速度,构建锚节点与待定位节点信息动态交互模型.在此基础上,构建基于信号传播时延(Round-trip Time,RTT)与接收信号强度(Received Signal Strength Indication,RSSI)动态定位模型,再引入波动系数作为调节因子,利用模糊推理规则建立RTT与RSSI相融合的动态定位模型,提出模糊推理下多模型融合的异步测距定位算法.仿真实验表明,改进算法与对比算法相比,考虑了水下节点的移动性,降低了水声信道的不稳定性对定位精度的影响,定位误差降低了25.58%,抗干扰能力显著提高.

Due to the mobile characteristics of underwater nodes moving with ocean currents,the existing underwater ranging and positioning algorithms have some problems such as low positioning accuracy and poor anti-jamming ability.To solve these problems,proposes an multi-model fusion clock asynchronous range location algorithm based on fuzzy reasoning.Firstly,use the deep sea Lagrange current model to describe the motion law of underwater nodes,simulate the motion speed of nodes.Then,build the dynamic interaction model of anchor nodes and unlocated nodes.On this basis,build a dynamic positioning model based on round-trip time(RTT)and received signal strength indentation(RSSI),and then import the fluctuation coefficient as the regulating factor.Based on fuzzy reasoning rules,the dynamic clock location model of RTT and RSSI fusion is established,and then propose the multi-model fusion clock asynchronous range location algorithm based on fuzzy reasoning.Simulation experiments show,compared with the comparison algorithm,the improved algorithm proposed takes the mobility of underwater nodes into consideration,reduces the influence of the instability of underwater acoustic channel on the positioning accuracy,reduces the positioning error by 25.58% and significantly improves the anti-interference ability.