基于洋流模型的水下传感器网络实时定位算法

针对近海监控领域内水下传感器网络的节点随着海洋运动具有流动性的问题,提出了基于洋流模型的水下传感器网络实时定位算法(RTLC).利用洋流模型表示节点的运动模型消除流动性对定位造成的影响,成功模拟了节点在水中的移动速度.通过卡尔曼预测方法结合观测值与估计值优化运动模型,使其更贴近节点运动规律.采用信息记录机制及列表更新机制保证信息的时效性从而提高了定位准确度.通过仿真分析,RTLC算法性能优于基于移动预测的大规模水下传感器网络可扩展定位算法(SLMP),具有较高的定位覆盖度,较低的平均定位误差及平均通信能耗.

Real-time localization algorithm based on current model for underwater sensor networks

To solve the problem that nodes move with ocean currents in underwater wireless sensor networks (UWSNs),a real-time localization algorithm based on current model (RTLC)is proposed.Using current model to represent mobility model of nodes eliminates the influence of fluidity on positioning and the speed of nodes underwater is simulated precisely.The mobility model is optimized by Kalman prediction combined observed values with theoretical values.Besides these,the recording and updating mechanism ensure information efficiency,so as to increase positioning accuracy.The simulation analysis shows that the performance of RTLC algorithm is prior to scalable localization with mobility prediction (SLMP) algorithm with low communication costs,high localization coverage rate and average positioning error.