We consider the distortion of nuclear magnetic resonance line in a quantum rotation sensor caused by the feedback in the cell during the detection of nuclear magnetization. Detection circuit is based on Faraday effect during longitudinal electronic paramagnetic resonance in alkali metal vapor.

Formulas for the unbalance components of the hemispherical resonator gyro (HRG) with a shell of thickness variable in the meridional direction are obtained. Various laws of thickness reduction from the pole to the edge are considered. It is shown that for the second form of excited oscillations, relative error in unbalance components (with the thickness variation neglected) can reach 10-15%. The obtained formulas for unbalance components, taking into account the variable thickness of the shell, can significantly improve the accuracy of HRG balancing, which is the most important process in the manufacture of medium and high precision devices.

An algorithm of a vertical gyroscope with MEMS sensors used to detect pitch and roll angles of aircraft is considered. It is suggested to integrate inertial sensors with an air data system. A flight simulator is used to optimize the algorithm coefficients.

A procedure is proposed for studying the errors of MEMS accelerometer triad, which features reduced test duration as compared with traditional methods and allows estimation of mutual geometrical arrangement of sensors in the triad. The proposed approach consists in studying the static characteristics of sensors in oscillating angular motion mode and provides estimation of error coefficients in mathematical model of accelerometer readings along with location of accelerometer triad in the closed IMU casing. Results of studying the errors of MEMS accelerometer triad are presented.

This paper describes the effect of trajectory-signal phase distortion on the image received by millimeter-wave automobile synthetic aperture radars (SAR). Calculations of the requirements for the errors of the sensors included in a strapdown inertial system to provide the resultant image with acceptable quality are given. Parameters of different accuracy-grade inertial sensors are analyzed; recommendations for choosing inertial sensors depending on SAR operating conditions and the required resolution are analyzed.

The Indian Regional Navigation Satellite System (IRNSS) is a seven-satellite constellation developed by Indian Space Research Organization (ISRO), India. IRNSS provides two services, with the standard positioning service open for civilian use, and for authorized users (including the military) with an assured absolute positional accuracy. IRNSS is designed to cover all the parts of India and also extending beyond the Indian borders. The coverage area of IRNSS with routes of satellites means and includes area covering entire Pakistan, Afghanistan, most of China and Middle East along with Indian Ocean. IRNSS downlink signals have two bands: S1 band and L5 Band. Presently Indian users are dependent on the civil GPS signals with a positional accuracy of 5 m. IRNSS system is intended to provide an absolute position accuracy of better than 10 m throughout Indian landmass better than 20 m over the Indian Ocean and approximately in a region of 1,500 km around India. There are 15 ground stations across the country responsible for operating and/or monitoring the IRNSS seven satellite constellation. A comparative analysis of IRNSS and GPS navigational satellites shows that the IRNSS consists of sufficient number of satellites for regional navigation system and it can also exhibit better performance. The main parameters selected for our study are orbital characteristics, position accuracy and positional error including Circular Error Probable (CEP), Altitude variation, Geometric Dilution of Precision (GDOP) with respect to Number of Satellites (NSAT), variations in Carrier to Noise (C/N0) ratio and scintillation effect of both GPS and IRNSS satellite systems. Our analysis showed that IRNSS systems shall be used as stand-alone system.

Local threats such as radio frequency interference, multipath and spoofing have attracted the attention of many researchers in the past years thus leading to a myriad of contributions in the field of threat detection. Nevertheless, the current state of the art relies on classical detection techniques, which are not well suited for threat detection. In this paper, we take a leap forward by adopting the so-called quickest detection framework. This approach fits perfectly in critical applications where the aim is to detect the presence of local threats as soon as possible in order to improve the integrity of GNSS receivers.

This paper describes an approach for fusion of monocular vision measurements, camera motion, odometer and inertial rate sensor measurements. The motion of the camera between successive images generates a baseline for range computations by triangulation. The recursive estimation algorithm is based on extended Kalman filtering. The depth estimation accuracy is strongly affected by the mutual observer and feature point geometry, measurement accuracy of observer motion parameters and line of sight to a feature point. The simulation study investigates how the estimation accuracy is affected by the following parameters: linear and angular velocity measurement errors, camera noise, and observer path. These results impose requirements to the instrumentation and observation scenarios. It was found that under favorable conditions the error in distance estimation does not exceed 2% of the distance to a feature point.

piNAV L1 is a GPS L1 receiver for position determination of the small satellites at LEO orbits. The receiver was tested by the ReGen software GPS simulator for static and dynamic scenarios. The typical horizontal position error for static scenario is 2.5 m (95%). The position errors for dynamic scenarios are affected by the dynamic stress errors.

The paper focuses on a ship motion prediction method. Unlike the other approaches, this prediction method with extended prediction duration uses dynamic models of the ship and disturbances. Identification procedure is used to determine the current parameters of ship motion dynamic model, and disturbance model is adjusted for certain motion conditions. Modeling results with the analyses are given, and the prediction of ship oscillation angle by the data obtained at the tests of a heavy aircraftcarrying cruiser.