OWP-IMU: An RSS-based Optical Wireless and IMU Indoor Positioning Dataset
원문 초록
Received signal strength (RSS)-based optical wireless positioning (OWP) systems are becoming popular for indoor localization because they are low-cost and accurate. However, few open-source datasets are available to test and analyze RSS-based OWP systems. In this paper, we collected RSS values at a sampling frequency of 27 Hz, inertial measurement unit (IMU) at a sampling frequency of 200 Hz and the ground truth at a sampling frequency of 160 Hz in two indoor environments. One environment has no obstacles, and the other has a metal column as an obstacle to represent a non-line-of-sight (NLOS) scenario. We recorded data with a vehicle at three different speeds (low, medium and high). The dataset includes over 110 k data points and covers more than 80 min. We also provide benchmark tests to show localization performance using only RSS-based OWP and improve accuracy by combining IMU data via extended kalman filter. The dataset OWP-IMU is open source1 to support further research on indoor localization methods.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
EnviKal-Loc: Sub-10m Indoor LoRaWAN Localization using an Environmental-Aware Path Loss and Adaptive RSSI Smoothing
A Statistical Evaluation of Indoor LoRaWAN Environment-Aware Propagation for 6G: MLR, ANOVA, and Residual Distribution Analysis
Visual Re-Ranking with Non-Visual Side Information
AI-Driven Relocation Tracking in Dynamic Kitchen Environments
PALMS: Plane-based Accessible Indoor Localization Using Mobile Smartphones
wav2pos: Sound Source Localization using Masked Autoencoders
토론
이 논문과 연결된 포럼 글이 아직 없습니다.