Satellite Inertial Navigation Research Articles

Satellite/Inertial Navigation Integrated Navigation Method Based on Improved Kalman Filtering Algorithm

With the continuous development of positioning technology in today’s world, the accuracy requirements for navigation and positioning are also getting higher and higher. Global Positioning and Navigation System (GPS) can provide high-precision long-term navigation and positioning information. However, it has a strong dependence on the external environment, which means that it is easily disturbed by environmental changes and affects the accuracy of navigation and positioning and even leads to positioning failure. The inertial navigation system (INS) is an autonomous navigation system. It uses sensors to measure the specific force and angular velocity of the carrier for positioning and navigation, which means that it is less affected by the environment. However, the inertial navigation device will produce a certain initial error due to the restriction of the manufacturing level, and the error will increase with time, so the inertial navigation method is not suitable for long-term navigation. Therefore, it is of great practical significance to realize satellite/inertial navigation integrated navigation by combining the respective advantages of satellite navigation and inertial navigation methods and avoiding their respective disadvantages. This paper is aimed at studying the satellite/inertial navigation integrated navigation method based on the improved Kalman filter algorithm. The satellite inertial navigation integrated navigation experiment is carried out based on the improved Kalman filter algorithm. In the experiment, the noise reduction experiment of the designed satellite inertial navigation system was carried out by using the filtering noise reduction function of the improved Kalman filter algorithm, and the conclusion was drawn after the experiment. The navigation accuracy of the satellite inertial navigation system is improved by a total of 2 m after the improved Kalman filter algorithm is used to filter the noise reduction.

Model of Hybrid Satellite-Inertial Navigation System with Partial Structure

A mathematical model of a hybrid navigation system (GNS) consisting of a three-component block of linear newtonometers (accelerometers) physically simulating a vector-based measurer of non-gravitational nature forces and on-board GLONASS receivers that positioning a moving object in an ellipsoidal coordinate system is presented and investigated. The absence of a gyroscopic angular velocity sensors unit, traditional for the classical schemes of the inertial navigation method, and the presence of no more than two onboard satellite positioning devices (receivers) make it possible to characterize the considered GNS as a partial structure system. As a basic element of a mathematical model for estimating linear and angular parameters of an object’s motion, the developed procedure of multiple numerical differentiation of temporal data acquired from on-board satellite receivers, which functions stably irrespective of the magnitude of the discretization step of the problem in time, was used. The developed GNS makes it possible to qualitatively evaluate both the trajectory parameters (location, velocity, acceleration and forces causing the trajectory) as well as the parameters of the spatial orientation of the object (Euler-Krylov angles and its derivatives) with a two-positioning technique. The results of the computational experiment are given. The field of application of the research results is numerical-analytical planning of trajectories, determination of motion parameters and control of moving objects for various purposes and basing.

Model of a neural network inertial satellite navigation system capable of estimating the earth’s gravitational field gradient

A model for recognizing inertial and satellite data on an object’s motion that are delivered by a set of distributed onboard sensors (newtonmeters, gyros, satellite receivers) has been described. Specifically, the model is capable of estimating the parameters of the gravitational field.

Algorithms of gyro-free accelerometer-based satellite-inertial navigation system

Algorithms of gyro-free accelerometer-based satellite-inertial navigation system

Integrated system able to measure errors of satellite navigation system receivers

The report discusses the methodology of physical integration and characteristics of an integrated inertial satellite navigation system (ISNS). The report shows benefits of the physical integration method as compared with the traditional method of mathematical integration based on Kalman filter. Mathematical modelling, laboratory and flight tests allowed to state that ISNS is able to measure and remove the effect of systematic errors of GPS/GLONASS receivers on the accuracy of the integrated channel of navigation. The report presents results of the flight experiment for the measurement of errors of four types of GPS/GLONASS receivers.