基于UWB的无线传感器网络中的两步TOA估计法

为了设计一种以较小运算量获得较高测距精度的TOA(time of arrival)估计算法以适合节点运算能力有限的UWB(ultra wideband)无线传感器网络,提出了一种结合能量检测与匹配滤波的两步TOA估计方法.分析了该方法的工作原理,指出了第1步中DP(direct path)块检测成功率及第2步中匹配滤波门限因子设置的重要性.通过仿真对影响DP块检测成功率的两个因素,即DP块检测算法的选用和能量积分周期的设置进行了讨论.提出了依据能量采样序列中DP块与最小块比值DMR(DP to minimum energy sample ratio)动态设置匹配滤波门限因子的思想,并为其建立了数学模型.仿真结果表明,两步TOA估计方法在运算量比单一的基于匹配滤波的相干算法小很多的情况下,获得了比单一的基于能量检测的非相干方法更好的TOA估计性能,从而更适合应用于有低复杂度、低能耗设计需求的传感器节点中.

A Two-Step TOA Estimation Method for UWB Based Wireless Sensor Networks

In order to design a low-calculation and high-precision TOA (time of arrival) estimation algorithm for UWB (ultra wideband) based wireless sensor network (WSN), a two-step TOA estimation method which jointly employs energy-detection (ED) and match-filtering (MF) is proposed in this paper. Based on analyzing the principles of the two-step method, it is pointed out that the success rate of DP (direct path) block detection in the first step and the setting of MF-threshold-factor in the second step are the key issues that affect the performance of the method. Algorithm selection of the first step and setting of the energy integration interval, which are the two factors that affect the success rate of DP block detection, are discussed through simulations. The idea of DMR (DP to minimum energy sample ratio) based MF-threshold-factor selection is proposed, and the mathematical model of the relationship between DMRs and the optimal MF-threshold-factors are built. Results show that the proposed two-step method greatly outperforms the one-step energy-detection based non-coherent method, while largely decreases the computational complexity compared to the one-step match-filtering based coherent method, so that the two-step method is more appropriate for application to sensor nodes which need to be designed with low complexity and low power consumption.