Star sensor installation error calibration in stellar-inertial navigation system with a regularized backpropagation neural network

Zhang, Hao; Niu, Yanxiong; Lu, Jiazhen; Yang, Yanqiang

doi:10.1088/1361-6501/aac6a8

Cited by 6 publications

(3 citation statements)

References 19 publications

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“…erefore, installation error is the most important error source of star sensor, and it is necessary to analyze and model it [17]. Generally, the installation error of star sensor can be considered as a random constant or a first-order Markov process [10,17]. In this paper, the random constant is used to describe it; that is,…”

Section: State Equation Of Integrated Navigation Systemmentioning

confidence: 99%

Accurate Integrated Navigation Method Based on Medium Precision Strapdown Inertial Navigation System

Yang

Geping

et al. 2020

Mathematical Problems in Engineering

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A method of accurate integrated navigation for high-altitude aerocraft by medium precision strapdown inertial navigation system (SINS), star sensor, and global navigation satellite system (GNSS) is researched in this paper. The system error sources of SINS and star sensor are analyzed and modeled, and then system errors of SINS and star sensor are chosen as system states of integrated navigation. Considering that the output of star sensor is attitude quaternion, it can be regarded as an attitude matrix, then the equivalent attitude matrix is constructed by using the output of SINS, and the calculating equation of the equivalent attitude matrix is designed. Thus, one of the measurements of integrated navigation can be constructed by using the equivalent attitude matrix and the attitude matrix output of star sensor. According to the constraint conditions of the attitude matrix, the diagonal elements are selected as one of the measurements of integrated navigation, and the corresponding measurement equation is derived. At the same time, the velocity output and position output difference between SINS and GNSS is selected as the other measurement, and the corresponding measurement equation is also derived. On this basis, the Kalman filter is used to design an integrated navigation filtering algorithm. Simulation results show that although the medium precision SINS is used, the heading accuracy of this integrated navigation method is better than ±1.5′, the pitch and roll accuracy are better than ±0.9’, the velocity accuracy is better than ±0.05 m/s, and the position accuracy is better than ±3.8 m. Therefore, the integrated navigation effect is very significant.

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Section: State Equation Of Integrated Navigation Systemmentioning

confidence: 99%

Accurate Integrated Navigation Method Based on Medium Precision Strapdown Inertial Navigation System

Yang

Geping

et al. 2020

Mathematical Problems in Engineering

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“…Therefore, the heading angle measured by the dual antennas of GNSS needs to be added into the measurement equation of the real-time integrated navigation and restrains the navigation precision drift with time [11]. However, due to the existence of assembly error, the installation error angle in the heading between the INS and dual antennas must be generated, which will seriously reduce the navigation accuracy [12]. Thus, the installation error angle needs to be measured accurately.…”

Section: Introductionmentioning

confidence: 99%

Improved integrated navigation method of micro position and orientation system based on installation error angle calibration

Qu¹,

Li²,

Zhang³

2022

Meas. Sci. Technol.

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Micro Position and Orientation System (POS) is the motion compensation equipment of airborne remote sensing system, which is composed of Inertial Navigation System (INS) and Global Navigation Satellite System (GNSS) with double antennas. The INS/GNSS integrated navigation is the key technology to measure micro POS motion information. However, the installation error angle between INS and dual antennas will seriously reduce the navigation accuracy. To solve this problem, an improved integrated navigation method of micro POS based on installation error angle calibration is proposed. Firstly, the calibration method of installation error angle based on a high-precision POS and the dual antennas is presented. Then, the improved real-time navigation algorithm based on error angle compensation is established. Finally, the flight experiment results indicate that the proposed method can effectively improve the navigation accuracy compared to uncalibrated method, especially the attitude and velocity accuracies, which are improved by 36% and 27%, respectively.

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“…Moreover, some researchers have calibrated installation parameters using a neural network. To improve the calibration accuracy under large installation angle errors, Zhang et al presented a novel calibration approach using a regularized backpropagation neural network and achieved calibration without formula derivation and numerical calculation under both small and large installation angle errors [15]. In the related area of inertial navigation systems (INSs), the calibration of the installation parameters of star sensors has also received significant attention [16,17].…”

Section: Introductionmentioning

confidence: 99%

On-Orbit Calibration of Installation Parameter of Multiple Star Sensors System for Optical Remote Sensing Satellite with Ground Control Points

Wang

Zhu

2020

Remote Sensing

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Owing to the vibrations and thermal shocks that arise during the launch and orbit penetration process, the on-orbit installation parameters of multiple star sensors are different from the on-ground measured parameters, causing inconsistencies in the attitude determinations from different combination modes and seriously affecting the geometric accuracy of high-resolution optical remote sensing images. This study presents an on-orbit calibration approach for the installation parameters of a multiple star sensors system using ground control points (GCPs). Based on the on-ground installation parameters of the optical axes of conventional star sensors, a fiducial coordinate system is proposed as the calibration coordinate system. The installation parameters of the conventional star sensors are calibrated using the statistical characteristics of angles between axes of the star sensor and three fiducial vectors in the J2000 celestial coordinate system. Based on the GCPs, the relative fiducial parameters are calculated, and the installation parameter of unconventional star sensor is then calibrated with the relative fiducial parameters and statistical characteristics of angles. It can be used for high-resolution optical remote sensing satellite measuring with only two star sensors to unify the fiducial coordinate system. The proposed method is tested using simulated data and on-orbit measurement data. The results demonstrate that the proposed method can calibrate the optical axis of the star sensor without the restriction of the accuracy of horizontal axis. Moreover, the star sensor with a large installation angle error can be calibrated well using the proposed approach. The results of attitude determinations from different star sensor combination modes are consistent, and the geometric accuracy of the remote sensing images is significantly improved.

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Star sensor installation error calibration in stellar-inertial navigation system with a regularized backpropagation neural network

Cited by 6 publications

References 19 publications

Accurate Integrated Navigation Method Based on Medium Precision Strapdown Inertial Navigation System

Accurate Integrated Navigation Method Based on Medium Precision Strapdown Inertial Navigation System

Improved integrated navigation method of micro position and orientation system based on installation error angle calibration

On-Orbit Calibration of Installation Parameter of Multiple Star Sensors System for Optical Remote Sensing Satellite with Ground Control Points

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