Indoor Location Algorithm Based on Kalman Filter and Multi-Source Data Integration

For indoor location, an active RFID indoor location system is designed. The system is designed and implemented by using a RSSI-based ranging technology location algorithm. In this article, the author amended the RSSI ranging equation, proposed and implemented a way to extract and estimate the environmental parameters of specific application scenarios, and improved the accuracy of the RSSI ranging. After many statistical experiments, the results show that the system’s deviation can reach 10cm on the diagonal of the region, and about 30cm on the edge. Through statistical calculation, the average deviation of system position is about 10.6cm, which is a good location system of high precision. When implemented for different applications, this system has the advantages of simplicity and adaptability.

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Transmission of Signals Using White LEDs for VLC Application

MRS Advances ◽

10.1557/adv.2016.372 ◽

2016 ◽

Vol 1 (55) ◽

pp. 3661-3666 ◽

Cited By ~ 2

Author(s):

P. Louro ◽

V. Silva ◽

J. Costa ◽

M. A. Vieira ◽

M. Vieira

Keyword(s):

Optical Filter ◽

Visible Light Communication ◽

Indoor Navigation ◽

Optical Signals ◽

White Leds ◽

Indoor Location ◽

Optical Channels ◽

Wavelength Sensitivity ◽

Location Algorithm ◽

The Individual

ABSTRCTIn this paper a photodetector working as an active optical filter device is used to detect modulated visible optical signals for applications based on Visible Light Communication (VLC). The proposed application demonstrates the viability of indoor positioning using VLC technology established by the modulation of indoor ultra-bright RGB white LEDs. The signals of the internal red and blue chips of the white LEDs were modulated at specific frequencies and the generated photocurrent was measured by a pin-pin photodetector based on a-SiC:H/a-Si:H. This device operates as a visible optical filter with controlled wavelength sensitivity through the use of adequate optical biasing light. Thus it is able to detect different wavelengths which allow the detection of the individual components of the tri-chromatic white LED. This possibility is the basis for the indoor location algorithm. We demonstrate the possibility of decoding four transmission optical channels supplied by two different wavelengths of white LEDs modulated under different bit sequences. The identification of the signals received by the photodetector allows the location identification of the photodetector position and supplies indoor navigation.

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TOF Indoor Location Algorithm based on RBF Neural Network

Proceedings of the International Conference on Advances in Computer Technology, Information Science and Communications ◽

10.5220/0008097901280134 ◽

2019 ◽

Author(s):

Hongmei Zhao ◽

Jielei Zhao

Keyword(s):

Neural Network ◽

Rbf Neural Network ◽

Indoor Location ◽

Location Algorithm

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Hybrid Location Algorithm of TDOA / AOA Based on Extended Kalman Filter

10.1109/icct52962.2021.9658015 ◽

2021 ◽

Author(s):

Huiyao Jiang ◽

Kun Zhang ◽

Chong Shen ◽

Jia Zhu ◽

Liwen Xu

Keyword(s):

Kalman Filter ◽

Extended Kalman Filter ◽

Location Algorithm

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Research on Multi-Source Data Integration Based on Ontology and Karma Modeling

International Journal of Intelligent Information Technologies ◽

10.4018/ijiit.2019040105 ◽

2019 ◽

Vol 15 (2) ◽

pp. 69-87 ◽

Cited By ~ 2

Author(s):

Hongyan Yun ◽

Ying He ◽

Li Lin ◽

Xiaohong Wang

Keyword(s):

Data Integration ◽

Armed Conflict ◽

Domain Knowledge ◽

Heterogeneous Data ◽

Regional Conflict ◽

Ontology Modeling ◽

Source Data ◽

Event Ontology ◽

Query System ◽

Rdf Data

The purpose of data integration is that integrates multi-source heterogeneous data. Ontology solves semantic describing of multi-source heterogeneous data. The authors propose a practical approach based on ontology modeling and an information toolkit named Karma modeling for fast data integration, and demonstrate an application example in detail. Armed Conflict Location & Event Data Project (ACLED) is a publicly available conflict event dataset designed for disaggregated conflict analysis and crisis mapping. The authors analyzed the ACLED dataset and domain knowledge to build an Armed Conflict Event ontology, then constructed Karma models to integrate ACLED datasets and publish RDF data. Through SPARQL query to check the correctness of published RDF data. Authors design and developed an ACLED Query System based on Jena API, Canvas JS, and Baidu API, etc. technologies, which provides convenience for governments and researches to analyze regional conflict events and crisis early warning, and it verifies the validity of constructed ontology and the correctness of Karma modeling.

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