Single and Double Reference Points Based High Precision 3D Indoor Positioning with Camera and Orientation-Sensor on Smart Phone

2015 ◽  
Vol 83 (3) ◽  
pp. 1995-2011 ◽  
Author(s):  
Honggui Li
Keyword(s):  
High Precision ◽  
Smart Phone ◽  
Indoor Positioning ◽  
Reference Points ◽  
Orientation Sensor

scholarly journals High-Precision RTT-Based Indoor Positioning System Using RCDN and RPN

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3701
Author(s):  
Ju-Hyeon Seong ◽  
Soo-Hwan Lee ◽  
Won-Yeol Kim ◽  
Dong-Hoan Seo
Keyword(s):  
High Precision ◽  
Distance Estimation ◽  
Sampling Period ◽  
Multipath Fading ◽  
Indoor Positioning ◽  
Positioning System ◽  
Positioning Systems ◽  
Positioning Errors ◽  
Location Determination ◽  
Indoor Positioning System

Wi-Fi round-trip timing (RTT) was applied to indoor positioning systems based on distance estimation. RTT has a higher reception instability than the received signal strength indicator (RSSI)-based fingerprint in non-line-of-sight (NLOS) environments with many obstacles, resulting in large positioning errors due to multipath fading. To solve these problems, in this paper, we propose high-precision RTT-based indoor positioning system using an RTT compensation distance network (RCDN) and a region proposal network (RPN). The proposed method consists of a CNN-based RCDN for improving the prediction accuracy and learning rate of the received distances and a recurrent neural network-based RPN for real-time positioning, implemented in an end-to-end manner. The proposed RCDN collects and corrects a stable and reliable distance prediction value from each RTT transmitter by applying a scanning step to increase the reception rate of the TOF-based RTT with unstable reception. In addition, the user location is derived using the fingerprint-based location determination method through the RPN in which division processing is applied to the distances of the RTT corrected in the RCDN using the characteristics of the fast-sampling period.

Autocorrelation Phase Measurement of Spread Spectrum Signal for High Precision Indoor Microwave Positioning

2015 ◽  
Vol 734 ◽  
pp. 31-39
Author(s):  
Wen Yang Cai ◽  
Gao Yong Luo
Keyword(s):  
High Precision ◽  
Spread Spectrum ◽  
Phase Measurement ◽  
Wide Band ◽  
Cost Effective ◽  
Local Area ◽  
Indoor Positioning ◽  
60 Ghz ◽  
Positioning Method ◽  
Increasing Demand

The increasing demand for high precision indoor positioning in many public services has urged research to implement cost-effective systems for a rising number of applications. However, current systems with either short-range positioning technology based on wireless local area networks (WLAN) and ZigBee achieving meter-level accuracy, or ultra-wide band (UWB) and 60 GHz communication technology achieving high precision but with high cost required, could not meet the need of indoor wireless positioning. This paper presents a new method of high precision indoor positioning by autocorrelation phase measurement of spread spectrum signal utilizing carrier frequency lower than 1 GHz, thereby decreasing power emission and hardware cost. The phase measurement is more sensitive to the distance of microwave transmission than timing, thus achieving higher positioning accuracy. Simulation results demonstrate that the proposed positioning method can achieve high precision of less than 1 centimeter decreasing when various noise and interference added.

scholarly journals IBPS: iBeacons Based Improved Indoor Positioning System

2020 ◽  
Vol 8 (5) ◽  
pp. 3792-3797
Keyword(s):  
Research Work ◽  
Energy Resource ◽  
Smart Phone ◽  
Indoor Positioning ◽  
Small Scale ◽  
Positioning System ◽  
Human Organ ◽  
Proposed Model ◽  
Small Hand ◽  
Indoor Positioning System

Smartphone plays a key role in integrating the entire world into a small hand. This feature made these smartphones as another human organ of many people. One of the main feature in every smart phone is GPS which used to travel new places, to locate and find optimized way to reach their destination. As we aware GPS is an outdoor application, GPS location is not accurate in indoor and small scale areas. This leads to an advanced research to improve the accuracy in GPS positing for the benefit of indoor applications. This research proposes a new iBeacons based Improved Indoor Positioning System for indoor positing application using Bluetooth low energy (BLE) beacons. This model helps the mobile application to find the exact location at micro-level scale. The objective of this research work is to design a potable indoor positing system (IPS) for indoor applications with at least 100m accuracy with in the inbuilt energy resource limitations. The proposed model has been built and verified in all the aspects. The location accuracy and energy efficiency of the proposed model is compared and found better than the existing models

scholarly journals Practical Fingerprinting Localization for Indoor Positioning System by Using Beacons

2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Santosh Subedi ◽  
Jae-Young Pyun
Keyword(s):  
Estimation Error ◽  
Indoor Positioning ◽  
Location Estimation ◽  
Reference Points ◽  
Ultra Wideband ◽  
Positioning System ◽  
Localization Method ◽  
Weighted Centroid Localization ◽  
Time Required ◽  
Indoor Positioning System

Recent developments in the fields of smartphones and wireless communication technologies such as beacons, Wi-Fi, and ultra-wideband have made it possible to realize indoor positioning system (IPS) with a few meters of accuracy. In this paper, an improvement over traditional fingerprinting localization is proposed by combining it with weighted centroid localization (WCL). The proposed localization method reduces the total number of fingerprint reference points over the localization space, thus minimizing both the time required for reading radio frequency signals and the number of reference points needed during the fingerprinting learning process, which eventually makes the process less time-consuming. The proposed positioning has two major steps of operation. In the first step, we have realized fingerprinting that utilizes lightly populated reference points (RPs) and WCL individually. Using the location estimated at the first step, WCL is run again for the final location estimation. The proposed localization technique reduces the number of required fingerprint RPs by more than 40% compared to normal fingerprinting localization method with a similar localization estimation error.

scholarly journals A Novel High Precision and Low Consumption Indoor Positioning Algorithm for Internet of Things

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 86874-86883 ◽  
Author(s):  
Jin Ren ◽  
Yunan Wang ◽  
Changliu Niu ◽  
Wei Song
Keyword(s):  
Internet Of Things ◽  
High Precision ◽  
Indoor Positioning ◽  
Positioning Algorithm ◽  
Low Consumption
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