Radar-Inertial Odometry with Online Spatio-Temporal Calibration via Continuous-Time IMU Modeling

• URL: http://arxiv.org/abs/2603.19958v1
• Date: Fri, 20 Mar 2026 14:00:58 GMT
• Title: Radar-Inertial Odometry with Online Spatio-Temporal Calibration via Continuous-Time IMU Modeling
• Abstract summary: Radar-Inertial Odometry (RIO) has emerged as a robust alternative to vision- and LiDAR-based odometry in challenging conditions.<n>We present a RIO framework that performs joint online spatial and temporal calibration within a factor-graph optimization formulation.<n>The proposed continuous-time representation of acceleration and angular velocity accurately captures the asynchronous nature of radar-IMU measurements.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Radar-Inertial Odometry (RIO) has emerged as a robust alternative to vision- and LiDAR-based odometry in challenging conditions such as low light, fog, featureless environments, or in adverse weather. However, many existing RIO approaches assume known radar-IMU extrinsic calibration or rely on sufficient motion excitation for online extrinsic estimation, while temporal misalignment between sensors is often neglected or treated independently. In this work, we present a RIO framework that performs joint online spatial and temporal calibration within a factor-graph optimization formulation, based on continuous-time modeling of inertial measurements using uniform cubic B-splines. The proposed continuous-time representation of acceleration and angular velocity accurately captures the asynchronous nature of radar-IMU measurements, enabling reliable convergence of both the temporal offset and extrinsic calibration parameters, without relying on scan matching, target tracking, or environment-specific assumptions.

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