水下传感器网络时间同步和定位的联合实现方法

水下传感器网络的信号传播速度受环境参数的影响而难以确定,增加了时间同步和定位的难度.当信号传播速度未知时,提出了一种水下传感器网络的时间同步和定位联合实现方案.通过建立该问题的优化函数和模型,设计了线性最小二乘(LLS)估计、最小二乘半定规划(LS-SDP)、平方最小二乘半定规划(SLS-SDP)及平方最小二乘二阶锥规划(SLS-SOCSDP)算法,分析了各算法的计算复杂度.仿真分析表明,线性代数LLS算法计算速度快,在低噪声条件下具有较高的估计精度.凸优化的LS-SDP、SLS-SDP及SLS-SOCSDP算法对未知参数估计的稳定性较好,但计算复杂度较高.

Joint Implement Approach for Time Synchronization and Localization in Underwater Sensor Networks

In underwater sensor networks,signal propagation speed is difficult to be determined due to the influence of environmental parameters,which increases the difficulty of time synchronization and localization. When the signal propagation speed is unknown,a joint implementation scheme for time synchronization and localization is put forward in underwater sensor networks. By building the optimization function and model of the problem, the linear least squares(LLS)estimation,least squares semidefinite programming(LS-SDP),squared least square semidefinite pro-gramming(SLS-SDP)and squared least square second order cone and semidefinite programming(SLS-SOCSDP)al-gorithms are designed,then the computational complexity of the proposed algorithms is analyzed. The simulation a-nalysis shows that the linear algebra LLS algorithm runs fast and obtains high positioning accuracy in low noise con-ditions. The stability of LS-SDP,SLS-SDP and SLS-SOCSDP algorithm with convex optimization is better,but the computation complexity is higher.