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Search Results (4)

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Keywords = spectral redshift navigation system

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18 pages, 4352 KB  
Article
A Novel SINS/SRS/CNS Multi-Information Fusion Global Autonomous Navigation Method
by Bin Zhao, Qinghua Zeng, Jianye Liu, Chunlei Gao, Xiaoling Zhu and Wei Qiao
Appl. Sci. 2022, 12(21), 10862; https://doi.org/10.3390/app122110862 - 26 Oct 2022
Cited by 6 | Viewed by 2111
Abstract
In order to improve the continuity and smoothness of transpolar flight and optimize autonomous navigation performance, a SINS/SRS/CNS (strapdown inertial navigation system/spectral redshift navigation system/celestial navigation system) multi-information fusion global autonomous navigation method based on parameter conversion was studied for this article. The [...] Read more.
In order to improve the continuity and smoothness of transpolar flight and optimize autonomous navigation performance, a SINS/SRS/CNS (strapdown inertial navigation system/spectral redshift navigation system/celestial navigation system) multi-information fusion global autonomous navigation method based on parameter conversion was studied for this article. The global autonomous navigation scheme based on multi-information fusion was designed. The principle of spectral redshift navigation was studied. On this basis, the system equations of the SINS/SRS/CNS multi-information fusion global autonomous navigation system were established in the middle–low latitudes and high latitudes. Furthermore, the navigation and filter parameter conversion relationships between the geographic navigation coordinate frame and the grid navigation coordinate frame were derived. The simulation and experiment verified that the SINS/SRS/CNS multi-information fusion global autonomous navigation method with parameter conversion can effectively improve the accuracy and smoothness and realize non-oscillation switching in transpolar navigation. In the vehicle experiment, the proposed algorithm improved the horizontal position accuracy by more than 29% compared with the multi-information fusion global autonomous navigation method without filter parameter conversion. Full article
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16 pages, 3034 KB  
Article
A Robust INS/SRS/CNS Integrated Navigation System with the Chi-Square Test-Based Robust Kalman Filter
by Guangle Gao, Shesheng Gao, Genyuan Hong, Xu Peng and Tian Yu
Sensors 2020, 20(20), 5909; https://doi.org/10.3390/s20205909 - 19 Oct 2020
Cited by 28 | Viewed by 4452
Abstract
In order to achieve a highly autonomous and reliable navigation system for aerial vehicles that involves the spectral redshift navigation system (SRS), the inertial navigation (INS)/spectral redshift navigation (SRS)/celestial navigation (CNS) integrated system is designed and the spectral-redshift-based velocity measurement equation in the [...] Read more.
In order to achieve a highly autonomous and reliable navigation system for aerial vehicles that involves the spectral redshift navigation system (SRS), the inertial navigation (INS)/spectral redshift navigation (SRS)/celestial navigation (CNS) integrated system is designed and the spectral-redshift-based velocity measurement equation in the INS/SRS/CNS system is derived. Furthermore, a new chi-square test-based robust Kalman filter (CSTRKF) is also proposed in order to improve the robustness of the INS/SRS/CNS navigation system. In the CSTRKF, the chi-square test (CST) not only detects measurements with outliers and in non-Gaussian distributions, but also estimates the statistical characteristics of measurement noise. Finally, the results of our simulations indicate that the INS/SRS/CNS integrated navigation system with the CSTRKF possesses strong robustness and high reliability. Full article
(This article belongs to the Collection Positioning and Navigation)
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16 pages, 6365 KB  
Article
A Strap-Down Inertial Navigation/Spectrum Red-Shift/Star Sensor (SINS/SRS/SS) Autonomous Integrated System for Spacecraft Navigation
by Zhaohui Gao, Dejun Mu, Yongmin Zhong and Chengfan Gu
Sensors 2018, 18(7), 2039; https://doi.org/10.3390/s18072039 - 26 Jun 2018
Cited by 22 | Viewed by 3707
Abstract
This paper presents a new Strap-down Inertial Navigation System/Spectrum Red-Shift/Star Sensor (SINS/SRS/SS) system integration methodology to improve the autonomy and reliability of spacecraft navigation using the spectrum red-shift information from natural celestial bodies such as the Sun, Jupiter and the Earth. The system [...] Read more.
This paper presents a new Strap-down Inertial Navigation System/Spectrum Red-Shift/Star Sensor (SINS/SRS/SS) system integration methodology to improve the autonomy and reliability of spacecraft navigation using the spectrum red-shift information from natural celestial bodies such as the Sun, Jupiter and the Earth. The system models for SINS/SRS/SS integration are established. The information fusion of SINS/SRS/SS integration is designed as the structure of the federated Kalman filter to fuse the local estimations of SINS/SRS and SINS/SS integrated subsystems to generate the global state estimation for spacecraft navigation. A new robust adaptive unscented particle filter is also developed to obtain the local state estimations of SINS/SRS and SINS/SS integrated subsystems in a parallel manner. The simulation results demonstrate that the proposed methodology for SINS/SRS/SS integration can effectively calculate navigation solutions, leading to strong autonomy and high reliability for spacecraft navigation. Full article
(This article belongs to the Section Physical Sensors)
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19 pages, 3124 KB  
Article
A SINS/SRS/GNS Autonomous Integrated Navigation System Based on Spectral Redshift Velocity Measurements
by Wenhui Wei, Zhaohui Gao, Shesheng Gao and Ke Jia
Sensors 2018, 18(4), 1145; https://doi.org/10.3390/s18041145 - 9 Apr 2018
Cited by 32 | Viewed by 7685
Abstract
In order to meet the requirements of autonomy and reliability for the navigation system, combined with the method of measuring speed by using the spectral redshift information of the natural celestial bodies, a new scheme, consisting of Strapdown Inertial Navigation System (SINS)/Spectral Redshift [...] Read more.
In order to meet the requirements of autonomy and reliability for the navigation system, combined with the method of measuring speed by using the spectral redshift information of the natural celestial bodies, a new scheme, consisting of Strapdown Inertial Navigation System (SINS)/Spectral Redshift (SRS)/Geomagnetic Navigation System (GNS), is designed for autonomous integrated navigation systems. The principle of this SINS/SRS/GNS autonomous integrated navigation system is explored, and the corresponding mathematical model is established. Furthermore, a robust adaptive central difference particle filtering algorithm is proposed for this autonomous integrated navigation system. The simulation experiments are conducted and the results show that the designed SINS/SRS/GNS autonomous integrated navigation system possesses good autonomy, strong robustness and high reliability, thus providing a new solution for autonomous navigation technology. Full article
(This article belongs to the Special Issue Sensor Fusion and Novel Technologies in Positioning and Navigation)
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