Inertial navigation is a device, which estimates its position, based on sensing external conditions (such as acceleration or angular velocity). It is widely used in variuos applications. Its presence in a drone vehicle for example, allows flight stabilization, by position estimation and feedback-based regulation algorithm execution. A smartphone makes a use of inertial navigation by detecting movement and flipping screen orientation. It is a ubiquitous part of many devices of everyday use, but before using filters and algorithms allowing to calculate the position, a calibration must first be applied to the device. This paper focuses on a separate calibration of each of the sensors - an accelerometer, gyroscope and magnetometer. The further step requires a cross–sensor calibration, and the third step is implementation of data filtration algotithm.

This paper investigates the noise levels present at various points in the FOSREM type fiber optic seismograph. The main aim of this research was to discover magnitudes of noise, introduced by various components of the analog and optical circuits of the device. First, the noise present in the electronic circuit without any optics connected is measured. Further experiments show noise levels including the detector diode not illuminated and illuminated. Additional tests were carried out to prove the necessity of analog circuitry shielding. All measurements were repeated using three powering scenarios which investigated the influence of power supply selection on noise. The results show that the electronic components provide a sufficient margin for the use of an even more precise detector diode. The total noise density of the whole device is lower than 4⋅10−7 rad/(s√Hz). The use of a dedicated Insulating Power Converter as a power supply shows possible advantages, but further experiments should be conducted to provide explicit thermic confirmation of these gains.