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arXiv · 2507.16120

FTIN: Frequency-Time Integration Network for Inertial Odometry

Shanshan Zhang·Qi Zhang·Siyue Wang·Liqin Wu·Tianshui Wen·Ziheng Zhou·Ao Peng·Xuemin Hong·Lingxiang Zheng·Yu Yang
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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.

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Shanshan Zhang, Qi Zhang, Siyue Wang, Liqin Wu, Tianshui Wen, Ziheng Zhou, Ao Peng, Xuemin Hong, Lingxiang Zheng, Yu Yang. 2025-07-22. FTIN: Frequency-Time Integration Network for Inertial Odometry. https://arxiv.org/abs/2507.16120

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