Year: 2026
Type: conference-paper
Abstract: Inertial odometry (IO) leverages inertial measurement unit (IMU) signals for cost-effective localization. However, high IMU sampling rates introduce substantial redundancy that impedes IO’s ability to attend to salient components, thereby creating an information bottleneck. To address this challenge, we propose a cross-domain IO framework that fuses information from the frequency and time domains. Specifically, we exploit the global context and energy-compaction properties of frequency-domain representations to capture holistic motion patterns and alleviate the bottleneck. To the best of our knowledge, this is among the first attempts to incorporate frequency-domain feature processing into IO. Experimental results on multiple public datasets demonstrate the effectiveness of the proposed frequency–time-domain fusion strategy.
Authors: Shanshan Zhang, Qi Zhang, Siyue Wang, Liqin Wu, Tianshui Wen, Ziheng Zhou, Ao Peng, Xuemin Hong, Lingxiang Zheng, Yu Yang
Institution: Xiamen University
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4414413486