The 16th International Conference on Indoor Positioning and Indoor Navigation (IPIN 2026) will be held on October 5th–8th in Rome, Italy.
IPIN is an international conference focusing on indoor positioning, navigation, and related sensing technologies.
Three papers from our joint research with LY Corporation and Ritsumeikan University will be presented at IPIN 2026.
MIMO-Free AoA Localization for Uncooperative Wi-Fi Probe Requests Using Commodity Single-Input Receivers
Abstract:
Passive localization using Wi-Fi signals is useful for applications such as spatial crowd sensing, where devices need to be localized without explicit user participation. Existing passive approaches often rely on RSSI- or CSI-based fingerprinting, which requires site-specific data collection and maintenance, limiting scalability and practical deployment.
This paper presents a MIMO-free and fingerprint-free approach for localizing Wi-Fi probe request frames using commodity single-input receivers. Probe request frames, which are automatically transmitted by Wi-Fi-enabled devices, are passively captured by multiple receivers. The proposed method aligns probe request frames across receivers, processes CSI phase and amplitude features, filters corrupted measurements, and estimates the angle of arrival (AoA) using a lightweight 1D convolutional network. Multiple AoA estimates are then geometrically combined to localize the signal source without relying on a dense fingerprint database or specialized MIMO hardware.
Experiments in a real indoor environment demonstrate the feasibility of passive AoA-based localization using a small number of commodity receivers. The proposed method achieved a mean localization error of 0.541 m with three receivers and 0.683 m with two receivers, compared with 1.560 m for an RSSI-based passive localization baseline using three receivers.
This work builds on Shiyuan Zhuang’s dedicated research efforts throughout his master’s program at Institute of Science Tokyo. Congrats, Zhuang-san!
In addition, the following two papers will also be presented.
Motion Context-Based Adaptation for Voice Navigation in Indoor Exploration
This work investigates adaptive voice navigation for indoor exploration by considering the motion context of pedestrians.
EAU-FM: Environmentally Adaptive UWB-Fingerprints Maintenance
This work addresses adaptive maintenance of UWB fingerprints under environmental changes for robust indoor positioning.
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Presentation information
2026/10/7 (Wed) 11:00–12:40
Session 12: mmWave, Radar & Passive Sensing
Title: MIMO-Free AoA Localization for Uncooperative Wi-Fi Probe Requests Using Commodity Single-Input Receivers
Authors: Shiyuan Zhuang, Kota Tsubouchi, Nobuhiko Nishio, Masamichi Shimosaka
2026/10/7 (Wed) 14:00–15:20
Session 15: Semantic & Language-Driven Indoor Navigation
Title: Motion Context-Based Adaptation for Voice Navigation in Indoor Exploration
Authors: Shohei Yoshinari, Kota Tsubouchi, Hirotaka Noda, Yuuki Nishiyama, Masamichi Shimosaka, Nobuhiko Nishio
2026/10/7 (Wed) 16:00–17:40
Session 16: UWB Ranging & Positioning
Title: EAU-FM: Environmentally Adaptive UWB-Fingerprints Maintenance
Authors: Kotaro Ikunishi, Yuki Hirayama, Daichi Kawanishi, Kota Tsubouchi, Masamichi Shimosaka, Nobuhiko Nishio