The most important properties of the satellite navigation, including world-wide availability, low dependence on weather conditions, possibility to measure at any point on the globe and of the near-earth space, allow its successful use in control loop of observation satellites and provision of their autonomous operation. The article deals with problems of substantiating the configuration and composition of observation satellites’ satellite navigation using radio navigation signals from global navigation satellite systems.

The paper offers solution to a problem of geostationary spacecraft navigation through navigation satellite signal measurements using nonlinear dynamic equations, which include such perturbing factors as non-sphericity of the gravitational field of the Earth, gravitational attraction of the Moon and the Sun, and direct solar radiation pressure. This solution uses the iterative Kalman filter based on UDdecomposition and is focused on the on-board implementation with limited computing resources. The estimates of current coordinates and velocity components obtained with the Kalman filter are taken into account when integrating nonlinear equations of a spacecraft motion up to the next solution time moment. In terms of accuracy requirements for the spaceborne satellite navigation receiver including the undetermined solar radiation pressure coefficient, the efficiency of the proposed solution was confirmed using the signal simulator and a GPS receiver.

The paper investigates spectral characteristics of modern global models of the Earth gravity field, obtained from space gravimetry missions CHAMP, GRACE and GOCE. The resolution is estimated for the given accuracy.

Proposals aimed at providing compatibility and complementarity of the RTK and the PPP methods for precise positioning of mobile objects using low-cost GLONASS/GPS equipment are presented. The proposals allow starting wider introduction of the most advanced methods without a need for updates of the existing GNSS ground infrastructure.

The paper considers the methods improving the mechanical performance of MEMS gyros. A multiaspect classification is proposed for systematizing data on mechanical performance of various gyro designs, and new perspective design principles are revealed

The paper considers the construction of geographically oriented horizon trihedral used to determine the object position by navigation dead-reckoning. In most cases, GOCP (gyroscopic orientation with corrected pendulum) method proposed by the author is more preferable than the inertial method. In GOCP method, the error in dead-reckoned coordinates caused by the construction of horizon plane using the readings of accelerometers disturbed by inertial accelerations can be inertialessly corrected using external velocity aiding. High-precision dead-reckoning is implemented using an accelerometer triad and one gimballess electrostatic gyro. This design serves both as an example of practical implementation and as a prototype of a class of single-gyro orientation systems used to aid navigation dead-reckoning.

This paper proposes a novel method for position determination by using neuro-fuzzy modeling and gravity gradient instrument data, which also can serve as a navigation aid to inertial navigation system using a Kalman filter. Since great majority of changes in gravity gradients are due to terrain, terrain elevation data are just used to model the gravity gradients at test location. To demonstrate the potential performance of this method, two cases including rough and smooth terrain are investigated, and impressive navigation accuracy is produced. Also the suitability of the proposed method for the use in different altitudes is compared.

In areas with insufficient GPS reception, like in urban areas close to buildings, alternative techniques have to be used to assist the inertial navigation system. The longterm objective of this work is to use buildings, detected in camera images, as distinctive landmarks for navigating micro aerial vehicles within the aforementioned areas. This paper presents a new method to detect buildings in aerial images. To use this algorithm onboard the vehicle during the mission, it has to be fast and executed automatically without readjusting any parameters by the operator. To cover a wide range of possible application areas, no building constraints are required. Therefore a wide variation of buildings with complex shapes can be detected.

The problem of identifying parameters of a model for a moving vehicle under external disturbances is considered. The latter are known to significantly affect the accuracy of model parameters. An approach to identification of model parameters under external disturbances is proposed. Estimates of the parameters are generated using an iterative procedure involving estimation of the vehicle state vector, which includes disturbance, and estimation of the vehicle model parameters using the method of least squares. The identified parameters are sufficiently stable to various external disturbances. The simulation results of the proposed approach are given. The approach was tested at full-scale tests.

We consider a classical optimal age replacement problem and generalize it to the case when an operating system is characterized by the corresponding deterministic penalty function. We apply this setting to navigation-information systems where the penalty is defined by the quality of its performance, namely, by the accuracy of the corresponding navigational characteristics. Three optimization models are considered and discussed. Some simple examples illustrating the obtained results are given.

Precision measurement of the small-signal parameters for embedded electronics inside real-time systems is actually today. Application of the non-linear measurement scales permits to achieve many opportunities versus linear case for embedded electronics. At first, decreasing of the full relative error of measurements. At work it is proved that for special case of non-linear functional scale (N = kXn ) at n < 1 full relative error less than for linear scale, i.e. at n = 1. The hardware model of nonlinear measuring channel was developed and experiments with nanoampere current source were carrying out. The main results of these experiments confirm theoretical assumptions about order of errors. Besides this model is able to work into wide range of value of input currents, this range is 1000 – from 1 nA to 1 μA. Our method and circuitry for non-linear small current measurements may base for future VLSI multichannel meters inside service electronics of inertial sensors.