一种高效的大监控区域移动目标追踪算法

针对目前无线传感器网络中利用位置指纹进行移动节点室内追踪时，为提高追踪精度引入的训练及匹配计算量大的问题，提出了一种兼顾定位精度和计算效率的算法。该算法适合锚节点稀疏分布的大监控区域，通过锚节点和参考位置点的局部匹配降低指纹匹配的复杂度，利用加权K-近邻算法获得粗定位，再通过融合目标节点加速度信息的卡尔曼滤波进一步减少追踪误差。仿真实验表明，本文算法具有良好的定位一致性和较高的定位精度，在指纹间隔10 m，接收信号强度指示值的测量方差高达16时，追踪过程中平均定位误差为1.4 m，适合室内移动目标的实时追踪。

An Efficient Method for Target Tracking in Large Area

Aiming to decrease the time complexity of both the train and the prediction process in indoor target tracking using radio fingerprints in wireless sensor networks, a novel method is proposed in this paper, which is an ideal solution for portable devices tracked in large area. A local match of the anchors and reference positions is introduced before applying the weighted K-nearest neighbors, which significantly decreases the complexity of positioning target. The Kalman filter is used forward with the previous positioning based on acceleration information to further increase the estimation accuracy. The performance of the method is studied thoroughly, indicating an average tracking accuracy of 1.4 m with the reference positions uniformly distributed at 10 m distance and the noise standard deviation of 16. Result shows that the proposed method is applicable for mobile target tracking in indoor environment.