Scientific paper ID 1738 : 2018/3

ADIS 16405 sensor is a complete inertial system. Sharing common housing there are triaxial inertial sensor, gyroscope and magnetometer based on MEMS technology. In spite of low inherent cost, small size, low power consumption, and solid reliability, when used by inertial systems for navigation or object’s dynamic parameters measurement it is highly important the random errors in the output signal to be appropriately treated and reduced. It is well known that Inertial Navigation Systems can provide high accuracy information on the position, velocity, and attitude over a short time period. However, their accuracy degrades rapidly with time. The ments for accurate estimation of navigation information necessitate the modeling of the sensors’ noise components. The error analysis can be conducted in the time domain specifying the stochastic variation as well as error sources of systematic nature. The article gives a resume of different noise types as well as methods for their assessment. Collected sensor’s experimental data was used to quantitative assess different noise types detected and gives an example of effectiveness of the chosen Allan variance error modeling method. It is simple to compute and relatively simple to interpret and understand. Allan variance method can be used to determine the character of the underlying random processes that give rise to the data noise. This technique can be used to characterize various types of noise terms in the inertial sensor data by performing certain operations on the entire length of data.