Position Estimation of Radio Source Based on Fingerprinting With Physical Wireless Parameter Conversion Sensor Networks
Position Estimation of Radio Source Based on Fingerprinting With Physical Wireless Parameter Conversion Sensor Networks
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DOI：
10.1109/access.2023.3242611
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发表时间：
2023-01-01
期刊：
影响因子：
3.9
通讯作者：
Adachi, Koichi
中科院分区：
文献类型：
--
作者：
Oda, Masafumi;Takyu, Osamu;Adachi, Koichi
为无线电波监测和频谱共享建立无线电源的高度精确定位正引起相当大的关注。由于定位方法一般需要对位置目标进行特定的处理，因此在位置目标无法进行任何处理时不适用。位置指纹识别方法使用多个传感器来观察由无线电源发射的接收信号强度指示（RSSI），并根据无线电波传播特性来估计位置。这不需要对目标位置进行一定的处理。然而，通过无线通信从许多传感器收集RSSI需要时间。在这项研究中，我们提出了一种RSSI收集方法，使用物理无线参数转换传感器网络（PhyC-SN）的无线电源的高速定位。在所提出的方法中，每个传感器选择对应于其测量的RSSI的无线电载波频率，并发送信号。将每个传感器的RSSI分布投影到接收信号的频率分布上，使得中心能够同时检测多个传感器的RSSI。为提高数据采集精度，考虑区域特征，建立了传感器分组方法，并基于每个传感器组进行访问时序控制。计算机仿真和实验结果表明，与传统的分组通信相比，该方法大大缩短了数据采集时间，并具有较高的定位精度。
Establishing a highly accurate positioning of radio sources for radio wave monitoring and frequency spectrum sharing is attracting considerable attention. Because the positioning method generally requires specific processing of the position target, it is not applicable when the position target cannot perform any processing. The location fingerprinting method uses multiple sensors to observe the received signal strength indication (RSSI) emitted by a radio source and estimates the position from the radio wave propagation characteristics. This does not require a certain process for the target position. However, it takes time to gather RSSI from many sensors by wireless communication. In this study, we propose an RSSI gathering method using physical wireless parameter conversion sensor networks (PhyC-SN) for the high-speed positioning of radio sources. In the proposed method, each sensor selects the radio carrier frequency corresponding to its measured RSSI and transmits the signal. Projecting the RSSI distribution of each sensor onto the frequency distribution of the received signal enables the center to detect the RSSI of multiple sensors simultaneously. Furthermore, to improve the gathering accuracy, we established a sensor group method by considering the regional characteristics and access timing control based on each sensor group. Computer simulations and experimental evaluations show that the proposed method significantly reduces the data-gathering time compared with conventional packet communications and achieves a high positioning accuracy.