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Barom etric altim eter in wireless com m unication network indoor positioning system

Journal of Beijing Institute of Technology 2013年第3期22卷 380-386页

作者：胡正群张丽荣 National Astronomical Observatories Chinese Academy of Sciences Graduate University of Chinese Academy of Sciences

A differential barometric altimetry technology based on the digital pressure sensors is put forward by using the existing mobile phone base station as reference. The height of known base sta- tion is precise. The pressure and temperature of the known base station is measured by sensors and transmitted to users. The absolute height value of user will be calculated by combining the baromet- ric pressure values and temperature values from the base station with the locally measured values. In order to decrease system errors caused by inconsistency between the measured pressure value at base station and the locally measured pressure value, weights correction is applied based on multiple reference stations. The calculated height value is accurate due to eliminating the measured errors caused by irregular changes of atmospheric pressure, with the error less than 1 m. Resolution of ele- vation positioning depends upon the resolution of the pressure sensor, the relationship between which is approximately linear. When the resolution of sensor is 0.01 hPa, the resolution of elevation positioning is about 0. 1 m. In addition, the data frame format at base station is designed in this arti- cle. Experimental results show that the method is accurate, reliable, stable and has the ability to distinguish floors and stair steps.

关键词： differential barometric altimetry wireless communication indoor positioning system micro-electro mechanical system (MEMS) MS5534C BP5607

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Robust Fingerprint Construction Based on Multiple Path Loss Model (M-PLM) for indoor Localization

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Computers, Materials & Continua 2023年第1期74卷 1801-1818页

作者： Yun Fen Yong Chee Keong Tan Ian Kim Teck Tan Su Wei Tan School of Information Technology Monash University MalaysiaSubang JayaSelangorMalaysia School of Mathematical and Computer Sciences Heriot-Watt University MalaysiaWilayah Persekutuan PutrajayaMalaysia

A robust radio map is essential in implementing a fingerprint-based indoor positioning system(IPS).However,the offline site survey to manually construct the radio map is time-consuming and *** interpolation techniques have been proposed to infer the virtual fingerprints to reduce the time and effort required for offline site *** paper presents a novel fingerprint interpolator using a multi-path loss model(MPLM)to create the virtual fingerprints from the collected sample data based on different signal paths from different access points(APs).Based on the historical signal data,the poor signal paths are identified using their standard *** proposed method reduces the positioning errors by smoothing out the wireless signal fluctuations and stabilizing the signals for those poor signal *** consideringmultipath signal propagations from different APs,the inherent noise from these signal paths can be ***,locations of the signal data with standard deviations higher than the threshold are *** new fingerprints are then generated at these locations based on the proposed M-PLM interpolation function to replace the old *** proposed technique interpolates virtual fingerprints based on good signal paths with more stable signals to improve the positioning *** results show that the proposed scheme enhances the positioning accuracy by up to 44%compared to the conventional interpolation techniques such as the Inverse DistanceWeighting,Kriging,and single Path *** a result,we can overcome the site survey problems for IPS by building an accurate radio map with more reliable signals to improve indoor positioning performance.

关键词： Path loss model radio map indoor positioning system interpolation fingerprinting

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Enhanced Fingerprinting Based indoor positioning Using Machine Learning

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Computers, Materials & Continua 2021年第11期69卷 1631-1652页

作者： Muhammad Waleed Pasha Mir Yasir Umair Alina Mirza Faizan Rao Abdul Wakeel Safia Akram Fazli Subhan Wazir Zada Khan Department of Electrical Engineering National University of Sciences and TechnologyIslamabad44000Pakistan Department of Computer Engineering National University of Modern Languages(NUML)Islamabad44000Pakistan Faculty of Computing Capital University of Science and TechnologyIslamabad44000Pakistan

Due to the inability of the Global positioning system(GPS)signals to penetrate through surfaces like roofs,walls,and other objects in indoor environments,numerous alternative methods for user positioning have been *** those,the Wi-Fi fingerprinting method has gained considerable interest in indoor positioning systems(IPS)as the need for lineof-sight measurements is minimal,and it achieves better efficiency in even complex indoor *** and online are the two phases of the fingerprinting *** researchers have highlighted the problems in the offline phase as it deals with huge datasets and validation of Fingerprints without pre-processing of data becomes a *** learning is used for the model training in the offline phase while the locations are estimated in the online *** researchers have considered the concerns in the offline phase as it deals with huge datasets and validation of Fingerprints becomes an *** learning algorithms are a natural solution for winnowing through large datasets and determining the significant fragments of information for localization,creating precise models to predict an indoor *** training sets are a key for obtaining better results in machine learning ***,an existing WLAN fingerprinting-based multistory building location database has been used with 21049 samples including 19938 training and 1111 testing *** proposed model consists of mean and median filtering as pre-processing techniques applied to the database for enhancing the accuracy by mitigating the impact of environmental dispersion and investigated machine learning algorithms(kNN,WkNN,FSkNN,and SVM)for estimating the *** proposed SVM with median filtering algorithm gives a reduced mean positioning error of 0.7959 m and an improved efficiency of 92.84%as compared to all variants of the proposed method for 108703 m^(2) area.

关键词： indoor positioning system fingerprinting received signal strength indicator mean position error support vector machine

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An indoor Autonomous Guided Vehicle Based on Electromagnetic Tracking and positioning Ibeacon

An Indoor Autonomous Guided Vehicle Based on Electromagnetic...

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第30届中国控制与决策会议

作者： Jiaping Luo Mingyun Chen Jiapeng Li Yongtao Wei Yuchen Hu Northeastern University at Qinghuangdao School of Control Engineering

In order to further improve the efficiency of indoor unmanned transport, a low-power and efficient navigation and positioning system is designed. The system combines the advantages of the detecting method of electromagnetic signals and the indoor positioning technology based on Bluetooth Low Energy(BTLE). By analyzing the magnetic field model, common inductance coils are used as a sensor to detect the magnetic field, and the differential steering mechanism of the motor is controlled by the tracking characteristics of the dual-inductive electromagnetic sensor. For GPS can not provide satisfactory indoor positioning results, on the basis of the electromagnetic tracking system combined with the indoor positioning technology based on spatial information mode, a stable and independent indoor positioning system is finally realized. And with the predetermined electromagnetic track crossing point, the dead reckoning accumulated error for signpost is revised. The experimental results show that the system can achieve stable operation, and the system design is reasonable and basically meets the design goals and users’ needs.

关键词： Electromagnetic Sensor RSSI indoor positioning system Electromagnetic Tracking Floyd Algorithm

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