Fingerprint Augmentation Based on Location Information Consistency in Dynamic Environment

IF 4.3 2区综合性期刊 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Sensors Journal Pub Date : 2024-10-31 DOI:10.1109/JSEN.2024.3486441

Wen Liu;XuDong Song;ZhongLiang Deng

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引用次数: 0

Abstract

The complex and dynamic structure of the indoor environment poses challenges for high-precision fingerprint localization. Changes in the indoor environment shift the data distribution domain of fingerprint data, leading to differences in data distribution between offline fingerprint databases and online data and reducing positioning accuracy. To address the time-consuming and labor-intensive task of reacquiring the database, we propose a method based on location information consistency for fingerprint data augmentation in dynamic environments. We treat fingerprint data of different changed environments as multiple domains and separate them into the location feature and the spatial feature by an encoder. The location feature represents the same statistical feature in different fingerprint data distributions, which is domain-invariant. The spatial feature corresponds to the unique statistical characteristics and random variations of each data distribution. Then, the generator is utilized to recombine the location feature with randomly sampled spatial features from the target spatial condition domain, generating diverse fingerprint samples of the target spatial conditions. Experimental results demonstrate that our method can effectively expand fingerprint data in dynamic environments and generate diverse outputs.

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动态环境下基于位置信息一致性的指纹增强

室内环境结构的复杂性和动态性为指纹的高精度定位提出了挑战。室内环境的变化使指纹数据的数据分布域发生了变化，导致离线指纹数据库与在线指纹数据库的数据分布存在差异，降低了定位精度。针对指纹数据库重新获取耗时费力的问题，提出了一种基于位置信息一致性的动态环境下指纹数据增强方法。我们将不同变化环境下的指纹数据视为多个域，并通过编码器将其分离为位置特征和空间特征。位置特征在不同的指纹数据分布中表示相同的统计特征，是域不变性的。空间特征对应于每个数据分布的独特统计特征和随机变化。然后，利用该生成器将位置特征与目标空间条件域中随机采样的空间特征进行重组，生成目标空间条件下不同的指纹样本。实验结果表明，该方法可以有效地扩展动态环境下的指纹数据，并产生多样化的输出。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Sensors Journal 工程技术-工程：电子与电气

CiteScore

7.70

自引率

14.00%

发文量

2058

审稿时长

5.2 months

期刊介绍： The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following: -Sensor Phenomenology, Modelling, and Evaluation -Sensor Materials, Processing, and Fabrication -Chemical and Gas Sensors -Microfluidics and Biosensors -Optical Sensors -Physical Sensors: Temperature, Mechanical, Magnetic, and others -Acoustic and Ultrasonic Sensors -Sensor Packaging -Sensor Networks -Sensor Applications -Sensor Systems: Signals, Processing, and Interfaces -Actuators and Sensor Power Systems -Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting -Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data) -Sensors in Industrial Practice