The Effect of Spatial Audio on the Virtual Representation of Personal Space

Buck, Lauren E.; Vargas, Mauricio Flores; McDonnell, Rachel

doi:10.1109/vrw55335.2022.00079

Cited by 5 publications

(1 citation statement)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Some existing technologies have already achieved indoor two-dimensional (2D) localization, for example, visual features [ 9 ], Light Detection and Ranging (LiDAR) [ 10 , 11 ], and wireless localization [ 12 ]. However, with the advancement of indoor three-dimensional (3D) localization sensor technology, emerging services like indoor drone control [ 2 , 13 ], virtual reality (VR) [ 14 , 15 ], or augmented reality (AR) [ 16 ] experiences demand higher accuracy in location. They also require more stringent height estimation and more frequent updates of information [ 17 , 18 ].…”

Section: Introductionmentioning

confidence: 99%

An Enhanced Indoor Three-Dimensional Localization System with Sensor Fusion Based on Ultra-Wideband Ranging and Dual Barometer Altimetry

Bao,

Li,

Lee

et al. 2024

Sensors

View full text Add to dashboard Cite

Accurate three-dimensional (3D) localization within indoor environments is crucial for enhancing item-based application services, yet current systems often struggle with localization accuracy and height estimation. This study introduces an advanced 3D localization system that integrates updated ultra-wideband (UWB) sensors and dual barometric pressure (BMP) sensors. Utilizing three fixed UWB anchors, the system employs geometric modeling and Kalman filtering for precise tag 3D spatial localization. Building on our previous research on indoor height measurement with dual BMP sensors, the proposed system demonstrates significant improvements in data processing speed and stability. Our enhancements include a new geometric localization model and an optimized Kalman filtering algorithm, which are validated by a high-precision motion capture system. The results show that the localization error is significantly reduced, with height accuracy of approximately ±0.05 m, and the Root Mean Square Error (RMSE) of the 3D localization system reaches 0.0740 m. The system offers expanded locatable space and faster data output rates, delivering reliable performance that supports advanced applications requiring detailed 3D indoor localization.

show abstract