Purpose

To solve the problem that the traditional received signal strength indicator real-time location method does not test the attenuation characteristics of the electromagnetic wave transmission in the location area, which cannot guarantee the accuracy of the location, resulting in a large location error.

Design/methodology/approach

At present, the compressed sensing (CS) reconstruction algorithm can be roughly divided into the following two categories (Zhouzhou and Fubao, 2014; Lagunas et al., 2016): one is the greedy iterative algorithm proposed for combinatorial optimization problems, which includes matching pursuit algorithm (MP), positive cross matching tracking algorithm (OMP), greedy matching tracking algorithm, segmented orthogonal matching tracking algorithm (StOMP) and so on. The second kind is the convex optimization algorithm, which also called the optimization approximation method. The common method is the basic tracking algorithm, which uses the norm instead of the norm to solve the optimization problem. In this paper, based on the piecewise orthogonal MP algorithm, the improved StOMP reconstruction algorithm is obtained.

Findings

In this paper, the MP algorithm (OMP), the StOMP and the improved StOMP algorithm are used as simulation reconstruction algorithms to achieve the comparison of location performance. It can be seen that the estimated position of the target is very close to the original position of the target. It is concluded that the CS grid-based target stepwise location method in underground tunnel can accurately locate the target in such specific region.

Originality/value

In this paper, the offline fingerprint database in offline phase of location method is established and the measurement of the electromagnetic noise distribution in different localization areas is considered. Furthermore, the offline phase shares the work of the location process, which greatly reduces the algorithm complexity of the online phase location process and the power consumption of the reference node, meanwhile is easy to implement under the same conditions, as well as conforms to the location environment.

中文翻译：

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基于压缩感知网格的地下隧道目标逐步定位方法

目的

解决了传统的接收信号强度指示器实时定位方法无法测试电磁波在定位区域内的衰减特性，无法保证定位精度，导致定位误差较大的问题。

设计/方法/方法

目前，压缩感知（CS）重建算法大致可分为以下两类（Zhouzhou and Fubao，2014; Lagunas et al。，2016）：一种是针对组合优化问题的贪婪迭代算法，其中包括匹配跟踪算法（MP），正交叉匹配跟踪算法（OMP），贪婪匹配跟踪算法，分段正交匹配跟踪算法（StOMP）等。第二种是凸优化算法，也称为优化近似方法。常用的方法是基本跟踪算法，该算法使用规范而不是规范来解决优化问题。本文基于分段正交MP算法，获得了改进的StOMP重构算法。

发现

本文将MP算法（OMP），StOMP和改进的StOMP算法用作仿真重建算法，以实现定位性能的比较。可以看出，目标的估计位置非常接近目标的原始位置。结论是，基于CS网格的地下隧道目标逐步定位方法可以在特定区域内准确定位目标。

创意/价值

本文建立了离线定位阶段离线指纹数据库，并考虑了不同定位区域电磁噪声分布的测量。此外，离线阶段分担了定位过程的工作，大大降低了在线阶段定位过程的算法复杂度和参考节点的功耗，同时在相同条件下易于实现，并符合位置环境。