An Efficient EM Algorithm for Energy-Based Multisource Localization in Wireless Sensor Networks
An Efficient EM Algorithm for Energy-Based Multisource Localization in Wireless Sensor Networks
复制标题
DOI：
10.1109/tim.2010.2047035
复制
发表时间：
2011-03-01
影响因子：
5.6
通讯作者：
Xie, Lihua
中科院分区：
文献类型：
--
作者：
Meng, Wei;Xiao, Wendong;Xie, Lihua
基于能量的多源定位是无线传感器网络中的一个重要研究课题。针对这一问题的现有算法，如多分辨率(MR)搜索法和穷举搜索法，要么计算复杂度高，要么估计精度低。针对无线传感器网络中基于能量的多源定位问题，提出了一种高效的最大似然(ML)估计算法。该算法的基本思想是将每个传感器的能量测量分解成分量，每个分量对应于一个单独的源，然后估计源的参数，如源能量和位置，以及信号在传播过程中的衰减因子。为了提高算法的速度和估计精度，提出了一种高效的序贯优势源(SDS)初始化方案和一种增量式参数化搜索求精方案。对算法的收敛速度、定位精度的Cramer-Rao下界以及算法的计算复杂度进行了理论分析。仿真结果表明，该EM算法在估计精度和计算复杂度之间取得了较好的折衷。
Energy-based multisource localization is an important research problem in wireless sensor networks (WSNs). Existing algorithms for this problem, such as multiresolution (MR) search and exhaustive search methods, are of either high computational complexity or low estimation accuracy. In this paper, an efficient expectation-maximization (EM) algorithm for maximum-likelihood (ML) estimation is presented for energy-based multisource localization in WSNs using acoustic sensors. The basic idea of the algorithm is to decompose each sensor's energy measurement, which is a superimposition of energy signals emitted from multiple sources, into components, each of which corresponds to an individual source, and then estimate the source parameters, such as source energy and location, as well as the decay factor of the signal during propagation. An efficient sequential dominant-source (SDS) initialization scheme and an incremental parameterized search refinement scheme are introduced to speed up the algorithm and improve the estimation accuracy. Theoretic analyses on the algorithm convergence rate, the Cramer-Rao lower bound (CRLB) for localization accuracy, and the computational complexity of the algorithm are also given. The simulation results show that the proposed EM algorithm provides a good tradeoff between estimation accuracy and computational complexity.