摘要
无线传感器网络(WSN)信源精确定位算法无法同步优化时延估计与角度估计,且不能将噪声子空间与信号子空间进行分割。为此,提出改进的WSN信源精确定位算法。采用并发方式构建信号解析机制,完成信号空间在频域域上的并发实时解析分割,将噪声信号子空间及信号子空间分割为独立的矩阵信号,获取信源精确定位的时延估计与角度估计。基于能量谱密度估计,设计正交复用循环机制,对单路信号进行特征值分解,得到定位信号数字特征的精确估计,提升时延估计与角度估计精度,并从该估计集合中筛选出同时具备最低时延估计与最低角度估计的信号子空间,从而完成时延与角度的并发实时估计,提高信源定位过程中的定位精度。仿真结果表明,与DT-IPL算法、CD-CPP算法相比,在高衰落信道条件下,该算法具有更高的信源定位精度,且获取的信源位置与实际位置间的误差更低。
In order to solve the current Wireless Sensor Network( WSN) source localization algorithms to synchronize and optimize time delay estimation and angle estimation,and it cannot segment noise and signal subspace,this paper proposes an improved source precise localization algorithm for WSN,it uses circulation mode to structure signal analysis mechanism, and implements the real time analysis segmentation of signal space in frequency domain,the noise of the signal subspace and the signal subspace is divided into matrix signal independent,the time delay estimation and the angle estimation of the source precise positioning are gained. Based on energy spectrum density estimation,orthogonal multiplexing cycle mechanism is designed,signal eigenvalue is decomposed,precise estimation of positioning signal features is achieved,the precision of the time delay and angle estimation is improved,and the signal subspace with minimum time delay estimation and the minimum angle estimation of space from the collection is filtered out,thus the algorithm completes the unified time delay estimation and angle estimation,improves the accuracy of source localization process. Simulation experimental results show that compared with the traditional DT-IPL algorithm,CD-CPP algorithm,this algorithm can significantly improve the positioning accuracy and the deviation between the source position and the actual position is low in high decline channel condition.
出处
《计算机工程》
CAS
CSCD
北大核心
2017年第11期81-89,共9页
Computer Engineering
基金
国家自然科学基金(41001251)
河南省重点科技攻关计划项目(102102310087)
河南省基础与前沿技术研究计划项目(112300410182)
关键词
无线传感器网络
信源定位
正交复用循环
信号子空间
时延估计
角度估计
Wireless Sensor Network (WSN)
singal source localization
orthogonal multiplexing cycle
signal subspace
time delay estimation
angle estimation