Towards no-drift sensors with on-chip self-calibration

Introduction

Sensor drift is a major problem for inertial sensors and limits their usage in autonomous navigation applications. Inertial sensor data is integrated to find the position, and drift leads to error accumulation.

Current Approaches

A common drift suppression approach is temperature calibration, but ovenized state-of-the-art sensors still exhibit drift. Instead of using temperature as a drift indicator, I have pursued a non-conventional approach and measured on-chip stress that directly correlates with drift.

Device Interaction

The device interacts with its surroundings through the anchors, and on-chip stress accurately estimates drift. I am the leading researcher in the stress compensation field, and I have recently demonstrated that MEMS gyroscope drift could be eliminated with stress compensation.

Stability Results

My long-term stability results at 2 days of averaging are unrivaled, but the calibration algorithm is not practical. Different from temperature calibration, stress calibrating a device is difficult.

Proposed Solution

I propose a sensor system that would convert my proof of concept work into a practical 0-drift sensor with self-calibration. The proposed system consists of:

1. A circular MEMS sensor with multiple (~100) distributed stress sensors and piezoelectric stress transducers
2. A machine learning supported analytical calibration model
3. A custom ASIC for superior noise
4. An FPGA for system control and self-calibration

Expected Outcomes

If successful, the proposed approach would improve the MEMS gyroscope stability by >100X to the levels of 10^-4 – 10^-5°/h, enabling error-free, only gravity-referenced inertial navigation.

Advantages of Inertial Navigation

Unlike GPS or camera, inertial navigation works under all weather, light, and location conditions, providing a stable reference to navigation algorithms.

Future Implications

With further miniaturization, 0-drift sensors could fit into smartphones, and reliable indoor navigation would become a reality. The compact, low-cost sensor could also disrupt the precision inertial market dominated by bulky and expensive fiber-optic and laser sensors.