arXiv subjects

Vasiliy M. Tereshkov

Publications and source records attributed to Vasiliy M. Tereshkov.

3 recordsLinked to original sources

arXiv2016

Closed-Loop Estimation of Oscillator g-Sensitivity in a GNSS/IMU System

We propose a simple method for estimating crystal oscillator g-sensitivity in inertially aided Global Navigation Satellite System (GNSS) receivers. It does not require any specific equipment, like GNSS signal simulators or rate tables. The method is based on analyzing closed-loop phase tracking errors. This enables us to utilize the actual GNSS signal as the frequency reference, despite the presence of an unknown Doppler shift in it. The method has been successfully applied to the calibration of an oven-controlled crystal oscillator.

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arXiv2015

A Simple Observer for Gyro and Accelerometer Biases in Land Navigation Systems

In various applications of land vehicle navigation and automatic guidance systems, Global Navigation Satellite System/Inertial Measurement Unit (GNSS/IMU) positioning performance crucially depends on the attitude determination accuracy affected by gyro and accelerometer bias instabilities. Traditional bias estimation approaches based on the Kalman filter suffer from implementation complexity and require non-intuitive tuning procedures. In this paper we propose, as an alternative, a simple observer that estimates inertial sensor biases exclusively in terms of quantities with obvious geometrical meaning. By this, any multidimensional vector-matrix operations are avoided and observer tuning is substantially simplified. The observer has been successfully tested in a farming vehicle navigation system.

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arXiv2013

An Intuitive Approach to Inertial Sensor Bias Estimation

A simple approach to gyro and accelerometer bias estimation is proposed. It does not involve Kalman filtering or similar formal techniques. Instead, it is based on physical intuition and exploits a duality between gimbaled and strapdown inertial systems. The estimation problem is decoupled into two separate stages. At the first stage, inertial system attitude errors are corrected by means of a feedback from an external aid. In the presence of uncompensated biases, the steady-state feedback rebalances those biases and can be used to estimate them. At the second stage, the desired bias estimates are expressed in a closed form in terms of the feedback signal. The estimator has only three tunable parameters and is easy to implement and use. The tests proved the feasibility of the proposed approach for the estimation of low-cost MEMS inertial sensor biases on a moving land vehicle.

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