一种传感网时间同步和定位的联合线性估计方法

A Joint Linear Estimation Approach for Time Synchronization and Localization in Wireless Sensor Networks

采用时间测量以估计节点位置的方法实现简单,在传感网中得到了广泛的使用。然而节点计时时钟存在漂移和偏离,导致时间测量不准确。为此文本以节点时钟漂移和偏离模型为基础,提出了一种时间同步和节点定位的联合线性估计方法,包括最小平方(LS)及权重最小平方(WLS)方法。仿真测试了所设计算法的运行时间,分析了噪声对联合估计方法的估计误差影响。结果表明,LS及WLS线性估计方法运算速度较半正定(SDP)算法快,在低噪声条件下LS及WLS线性估计方法具有较高的稳定性和定位精度。

It is simple to estimate the locations of sensor nodes by using the time measurements which are widely used in sensor networks. However there is a drift and deviation of the time clock, which leads to inaccurate time measurement. Based on the clock drift and deviation model, a joint linear estimation method for time synchronization and node localization is proposed, including the least squares （LS）and the weighted least squares （WLS）method. The simulations tested the running time of the designed algorithm and analyzed the impacts of the noises on the estimation error with the joint estimation method. The results show that the LS and WLS linear estimation algorithms run faster than the SDP algorithm, and the LS and WLS linear estimation methods have high stability and accuracy in low noise conditions.