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 Drift Suppression 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 and Stress Measurement

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 Sensor System

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.

Potential Impact

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 cameras, inertial navigation works under all weather, light, and location conditions, providing a stable reference to navigation algorithms. With further miniaturization, 0-drift sensors could fit into smartphones, and reliable indoor navigation would become a reality.

Market Disruption

The compact, low-cost sensor could also disrupt the precision inertial market dominated by bulky and expensive fiber-optic and laser sensors.