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Research on indoor positioning method based on LoRa-improved fingerprint localization algorithm.

Honghong Chen¹, Jie Yang², Zhanjun Hao²

¹College of Computer Science and Engineering, Northwest Normal University, Gansu, China. chenhh@nwnu.edu.cn.

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|August 26, 2023

Summary

This summary is machine-generated.

This study introduces an improved indoor localization method using LoRa, enhancing accuracy by combining signal strength and time-of-flight data. The algorithm significantly boosts localization precision for reliable positioning systems.

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Area of Science:

Wireless communication
Localization algorithms
Machine learning

Background:

Traditional fingerprint localization methods suffer from low accuracy, large data requirements, and device dependency.
Existing algorithms struggle with real-world indoor positioning challenges.

Purpose of the Study:

To propose an improved LoRa-based fingerprint localization algorithm for enhanced indoor positioning accuracy.
To address the limitations of traditional methods through novel data processing and machine learning techniques.

Main Methods:

A novel RSSI-RANGE fingerprint value combining Received Signal Strength Indication (RSSI) and Time of Flight (RANGE) was developed.
Gaussian and median filtering were employed for fingerprint data preprocessing to reduce errors.
Particle Swarm Optimization (PSO) optimized Random Forest (RF) hyperparameters for accurate fingerprint value extraction.
Kriging interpolation was used to build the offline fingerprint database.

Main Results:

The RSSI-RANGE method improved localization accuracy by 53-57%.
Data preprocessing enhanced accuracy by 25-31%.
The combined approach achieved a significant 58-63% improvement in localization accuracy.

Conclusions:

The proposed LoRa-based improved fingerprint localization algorithm effectively enhances indoor positioning accuracy.
Combining RSSI-RANGE data, advanced filtering, and optimized machine learning models offers a robust solution.
This method overcomes key limitations of traditional localization techniques.