Patrick Tritschler

Abstract

Fiber optic Sagnac interferometer can measure the rotation rate of a system with a high sensitivity. However, they require a large sensor area which leads to a huge footprint and size compared to their MEMS counterpart. Consequently, the performance decreases when using chip integrated Sagnac interferometers with small sensor areas. Here, we address this issue and present a method to improve the sensitivity at a small scale. Therefore, we utilize twomode squeezed light that can be generated in a ring resonator via four-wave mixing (FWM), which can have a very low noise. We show that the combination of classical coherent light and squeezed light can improve the sensor performance compared to a classical fiber optic Sagnac interferometer. For this purpose, we discuss two different configurations that are suited for various applications. The first one makes use of the low-noise of squeezed light and is suited for small and low loss systems using intensitiy difference (ID) measurements while the second one measures the variance of squeezed light via product detection (PD) and is suited for larger and lossy systems.

Abstract

The research presented in this work compensates non-orthogonality over temperature stress effects in low-cost open-loop MEMS gyroscopes using neural networks (NN) for a sensor individual compensation to improve the sensor performance. The non-orthogonality is included in the sensor cross-axis sensitivity (CAS) of MEMS gyroscopes. Using the model-agnostic meta-learning algorithm (MAML) as a self-calibration algorithm and one initial measurement after soldering, an individual compensation model is generated for each sensor that predicts the non-orthogonality using the MEMS gyroscope's quadrature value as an input. It will be shown that a sensor-individual model outperforms a compensation model that should fit for all sensors at once like linear regression or classic NN and improves the non-orthogonality by 82.7 %, 7.5 % and 70 % for yx-, zx-, and zy-non-orthogonality,

Abstract

Inertial measurement units (IMU) are able to sense the acceleration and rotation rate of a system and are widely used in mass products like mobile phones and toy drones. These different use-cases have various requirements on the IMU in dependency of the occurring environmental influences. These influences are for example stress effects like temperature, humidity or diverse soldering processes which cause the performance of the sensors to suffer. The initial sensor calibration during the manufacturing of the IMUs is not sufficient anymore and the individual further processing and usage reduces this performance. In this work, an approach that increases the performance and improves the stress robustness against environmental influences is presented. This approach self-calibrates each sensor part individually by using a machine-learning technique called meta-learning. This allows to efficiently adapt a general meta-model to different sensor units to achieve an improved stress robustness with only one data sample. While the quadrature signal of IMUs gyroscope is used to demonstrate the performance and behavior of the chosen approach, this method is applicable for a wide range of various sensor systems to speed up the calibration process and to increase the performance for multiple use-cases.

Abstract

This work shows the possibility to generate single-mode squeezed light using four-wave mixing in micro-ring resonators and determines the phase sensitivity in a lossy Mach-Zehnder Interferometer. It is shown that sub-shot noise measurements can be achieved.

Abstract

This work is concerned with the examination of one-dimensional stress effects in mode-split, open-loop MEMS gyroscopes with the goal to predict the sensitivity change under printed circuit board (PCB) bending stress. Measurements with ten triaxial gyroscopes are compared to simulation results based on a detailed analytical model. The dependencies of gap distance and overlap of the in- and out-of-plane detection capacitances related to bending stress are formulated. Sensitivity change is predicted with 75% accuracy and the sign of gradient is correct for all measurements. Besides the change in geometry parameters of capacitances the effects of mechanical bending stress on the entire system are discussed. The purpose of the paper is to show the fundamental relationships on which all further considerations regarding MEMS gyroscopes under PCB stress are built.