Tunable Virtual IMU Frame by Weighted Averaging of Multiple Non-Collocated IMUs

TL;DR

This paper introduces a method to create a virtual IMU by weighted averaging multiple spatially separated IMUs, reducing noise and enabling flexible placement, validated through simulation and real data.

Contribution

A novel quadratic programming approach for optimally weighting and positioning multiple IMUs into a single virtual IMU with noise reduction benefits.

Findings

Effective noise reduction through averaging multiple IMUs.

Performance improvement over single IMU setups.

Validated results in both simulation and real-world experiments.

Abstract

We present a new method to combine several rigidly connected but physically separated IMUs through a weighted average into a single virtual IMU (VIMU). This has the benefits of (i) reducing process noise through averaging, and (ii) allowing for tuning the location of the VIMU. The VIMU can be placed to be coincident with, for example, a camera frame or GNSS frame, thereby offering a quality-of-life improvement for users. Specifically, our VIMU removes the need to consider any lever-arm terms in the propagation model. We also present a quadratic programming method for selecting the weights to minimize the noise of the VIMU while still selecting the placement of its reference frame. We tested our method in simulation and validated it on a real dataset. The results show that our averaging technique works for IMUs with large separation and performance gain is observed in both the simulation and the real experiment compared to using only a single IMU.