GPS and navigation GPS)، GLONASS، GALILEO
Reza Ghasrizadeh; Amir Ali Nikkhah
Volume 16, Issue 3 , September 2023, , Pages 37-49
Abstract
This paper presents a solution for detecting and recovery for the spoof error of GPS receiver signals, in order to increase the accuracy of the navigation system integrating inertial systems with GPS signals. integrated inertial navigation and GPS data has many advantages. However, due to the weakness ...
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This paper presents a solution for detecting and recovery for the spoof error of GPS receiver signals, in order to increase the accuracy of the navigation system integrating inertial systems with GPS signals. integrated inertial navigation and GPS data has many advantages. However, due to the weakness of satellite signals against jamming and spoof attacks of providing analytical solutions, they have a special place in improving Kalman filter estimation compared to hardware solutions. In this paper, a new method for loosely coupled of INS/GPS is presented, in which the steady state of Kalman gain parameters is used during deception detection and recovery. With the gain parameters of the Kalman filter tending to constant values, with the aim of correcting and predicting the error of state variables, it can be used to detection GPS spoofed data. It can be detected by spoof in the GPS receiver signal when couple with inertial waves through the amount of Kalman gain fluctuations. In the case of closed loop, the Kalman gain matrix denominators tend to a constant value, and in case of deception, this function is associated with many fluctuations. By using dynamic weighting, the effect of errors caused by these attacks is recovered.
Space subsystems design: (navigation, control, structure and…)
M. Navabi; M. Salehi
Volume 16, Issue 2 , June 2023, , Pages 63-77
Abstract
In a flying system, attitude control is one of the essential subsystems. In this subsystem, estimating the current state is very important to control the state, which is achieved by considering the attitude sensors. Comprehensive research is being done today to reduce the cost of Attitude sensors in ...
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In a flying system, attitude control is one of the essential subsystems. In this subsystem, estimating the current state is very important to control the state, which is achieved by considering the attitude sensors. Comprehensive research is being done today to reduce the cost of Attitude sensors in applications such as drones, satellite simulation platforms, etc. For this purpose, sensors based on Micro-electromechanical Systems have received much attention due to their small size and low energy consumption. This model of sensors, despite its many advantages, has various noises and disturbances that require the application of fusion and estimation algorithms to obtain an acceptable output. In this research, to determine the attitude of the test platform, data fusion algorithms including complementary filter, Kalman filter, and Extended Kalman filter are implemented on a low-cost sensor. The mentioned estimation methods were implemented on the test platform and by determining the effective parameters in the estimation algorithms, the desired accuracy was obtained. The module obtained in these experiments is comparable to more expensive sensors.
Space systems design (spacecraft, satellites, space stations and their equipment)
Abbas Saeidi; Nasser Rahbar; Mohammad Ali Alirezapouri
Volume 14, Issue 3 , September 2021, , Pages 65-73
Abstract
In recent years, according to progress of aerospace industries particularly satellites it has been paying much attention to attitude determination of satellite. Attitude determination of satellite in various ways, such as: radio, radar, optical methods and using GPS, q and kalman filter is done, that ...
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In recent years, according to progress of aerospace industries particularly satellites it has been paying much attention to attitude determination of satellite. Attitude determination of satellite in various ways, such as: radio, radar, optical methods and using GPS, q and kalman filter is done, that each of these methods has advantages and disadvantages. Due to disturbance in space, high accuracy in attitude determination, various algorithms to obtain properly accurately attitude, desirable access to position, velocity and time of satellite to achieve desired attitude determination satellite are considered a top priority. However in this Paper, first we review the various methods for attitude determination satellite and then examine of operation and relations of algorithms discussed. This Paper focus on the advantages and disadvantages of qEKF algorithm in compare to other methods are available.
Remote sensing
Fereydon Nobakht Orsi; Abdolreza Safari; Amir Khodabandeh
Volume 14, Issue 3 , September 2021, , Pages 101-108
Abstract
In this paper, we discussed standard point positioning technique based on the single frequency code-based (C/A) receivers. Then, we presented its performance by means of different measures. However, the use of one single frequency GPS receiver to obtain high-precision positioning make a major challenge ...
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In this paper, we discussed standard point positioning technique based on the single frequency code-based (C/A) receivers. Then, we presented its performance by means of different measures. However, the use of one single frequency GPS receiver to obtain high-precision positioning make a major challenge due to the environmental biases, in particular the ionospheric effects are handled. The main objective of the present study is to integrate a inospheric model such as Klobuchar Inospheric Model (KIM) with imprecise code (C/A) observations under intense geomagnetic storm conditions, then, to obtain dm level positioning accuracy using Kalman filter. For this purpose we used code (C/A) observations on two different days (February 26, 2018 and December 20, 2015) at Tehran station. The results show that we could obtain multi-dm level positioning accuracy under geomagnetic storm condition by using Kalman filter that will be important in the field of kinematic applications.
Mehdi Fathi; ali mohammadi; Nemat Ollah Ghahramani
Volume 8, Issue 4 , January 2016, , Pages 45-51
Abstract
In this paper the feasibility of rapid alignment and calibration of a static strapdown inertial navigation system (INS) is evaluated. Resting conditions including zero-velocity update and a known initial heading direction as virtual external measurement data are integrated with INS data. By comparing ...
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In this paper the feasibility of rapid alignment and calibration of a static strapdown inertial navigation system (INS) is evaluated. Resting conditions including zero-velocity update and a known initial heading direction as virtual external measurement data are integrated with INS data. By comparing the virtual external measurements with the estimates of those generated by the aligning INS, estimates of the velocity and heading errors can be obtained and these errors will be propagated in the INS as a result of alignment inaccuracies. An extended Kalman filter based on an augmented process model and a measurement model is designed to estimate alignment attitudes and biases of inertial sensors. Monte Carlo simulation results show that the integration of INS with rest conditions is very effective in rapid and fine leveling and azimuth alignment of INS, but this type of data fusion due to poor acceleration and angular rates of static condition has no chance of valuable calibration of all inertial sensor biases.
M. Jafari; M. Taefi; J. Roshanian
Volume 6, Issue 2 , July 2013, , Pages 57-66
Abstract
Flight dynamic equations have an effective role in aerospace technologies. It can be as cheap and efficient means for correcting errors in the spatial position and velocity in inertial navigation systems. The Inertial navigation system is an ideal solution for motion detection with high accuracy with ...
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Flight dynamic equations have an effective role in aerospace technologies. It can be as cheap and efficient means for correcting errors in the spatial position and velocity in inertial navigation systems. The Inertial navigation system is an ideal solution for motion detection with high accuracy with fast dynamics, but the precise location and status of the system output can be significantly reduced over time. In this paper, inertial navigation system integrated with a navigation aided system based on online solving of flight dynamic equations. For this purpose, the proposed use of the Lagrangian of Kepler equations and three degrees of freedom of Newton's equations of transfer flights dynamic has been studied. Using this method, online high accuracy to be achieved by flight computer. Kalman filter algorithm is used for integrating inertial navigation and flight dynamic equations . Finally, The simulation results including position and velocity errors with regard to fly a prototype space module, for the proposed two conditions were compared and the advantages and disadvantages of each method are presented
Mahdi Jafari; Arash Sangary; Jafar Roshanyan
Volume 5, Issue 3 , October 2012, , Pages 11-19
Abstract
The Inertial navigation system is an ideal solution for motion detection with high accuracy with fast dynamics, but the precise location and status of the system output can be significantly reduced over time. On the other hand, global positioning system is able to determine its position with an average ...
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The Inertial navigation system is an ideal solution for motion detection with high accuracy with fast dynamics, but the precise location and status of the system output can be significantly reduced over time. On the other hand, global positioning system is able to determine its position with an average accuracy around the earth. But the GPS alone isn’t enough for navigation of orbital modules, because it doesn’t have situation of orbital modules. The integrated inertial navigation system with global positioning system is a low cost method of providing an accurate and reliable navigation system in the civilian and military aerospace applications. In this paper, using the extended Kalman filter, we design an algorithm to estimate error of sensors, navigation and GPS. This method can be widely used in the integrated navigation INS / GPS in aerospace applications and provides an accurate navigation.
H. Bolandi; F. Fani-Saberi
Volume 2, Issue 2 , July 2009, , Pages 17-26
Abstract
In this paper, a novel and highly accurate attitude estimation method for a LEO satellite is designed. The method is based on multiple model adaptive estimation (MMAE) structure. In this method, the satellite dynamic equation is linearized in a few points in order to increase the computational rate compared ...
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In this paper, a novel and highly accurate attitude estimation method for a LEO satellite is designed. The method is based on multiple model adaptive estimation (MMAE) structure. In this method, the satellite dynamic equation is linearized in a few points in order to increase the computational rate compared with extended Kalman filter (EKF) method. The attitude determination and control system of the satellite is consists of a star sensor, gyroscope and reaction wheels. As known, star sensor is a very power consuming sensor in attitude determination of the satellite; therefore, a lesser power consuming method, using the dynamic model of the satellite along with angular momentum of the reaction wheels, is proposed to estimate the satellite attitude. This method assures the proper operation and the attitude estimation of the satellite in eclipse mode as well. By applying this method, the star sensor is used for a short period of time which reduces power consumption considerably. The performance and effectiveness of the proposed algorithm are investigated through numerical simulations and is compared with extended Kalman filter.
