scholarly journals Multi-Slots Joint MLE Relative Navigation Algorithm Based on INS/JTIDS/BA for Datalink Network

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 136795-136807
Author(s):  
Shuo Cao ◽  
Honglei Qin ◽  
Li Cong ◽  
Yingtao Huang
Keyword(s):  
Relative Navigation ◽  
Navigation Algorithm

scholarly journals Multi-Satellite Relative Navigation Scheme for Microsatellites Using Inter-Satellite Radio Frequency Measurements

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3725
Author(s):  
Shiming Mo ◽  
Xiaojun Jin ◽  
Chen Lin ◽  
Wei Zhang ◽  
Zhaobin Xu ◽  
...  
Keyword(s):  
Radio Frequency ◽  
High Precision ◽  
Satellite Measurement ◽  
Relative Navigation ◽  
Measurement Scheme ◽  
Navigation Algorithm ◽  
Angle Measurements ◽  
Satellite Formations ◽  
Navigation Accuracy ◽  
Navigation Scheme

The inter-satellite relative navigation method—based on radio frequency (RF) range and angle measurements—offers good autonomy and high precision, and has been successfully applied to two-satellite formation missions. However, two main challenges occur when this method is applied to multi-microsatellite formations: (i) the implementation difficulty of the inter-satellite RF angle measurement increases significantly as the number of satellites increases; and (ii) there is no high-precision, scalable RF measurement scheme or corresponding multi-satellite relative navigation algorithm that supports multi-satellite formations. Thus, a novel multi-satellite relative navigation scheme based on inter-satellite RF range and angle measurements is proposed. The measurement layer requires only a small number of chief satellites, and a novel distributed multi-satellite range measurement scheme is adopted to meet the scalability requirement. An inter-satellite relative navigation algorithm for multi-satellite formations is also proposed. This algorithm achieves high-precision relative navigation by fusing the algorithm and measurement layers. Simulation results show that the proposed scheme requires only three chief satellites to perform inter-satellite angle measurements. Moreover, with the typical inter-satellite measurement accuracy and an inter-satellite distance of around 1 km, the proposed scheme achieves a multi-satellite relative navigation accuracy of ~30 cm, which is about the same as the relative navigation accuracy of two-satellite formations. Furthermore, decreasing the number of chief satellites only slightly degrades accuracy, thereby significantly reducing the implementation difficulty of multi-satellite RF angle measurements.

Relative Navigation Algorithm Using PSD and Heterogeneous Sensor Fusion

2020 ◽  
Vol 48 (7) ◽  
pp. 513-522
Author(s):  
Dongmin Kim ◽  
Seungwon Yang ◽  
Domyung Kim ◽  
Jinyoung Suk ◽  
Seungkeun Kim
Keyword(s):  
Sensor Fusion ◽  
Relative Navigation ◽  
Navigation Algorithm

A novel relative navigation algorithm for formation flight

2019 ◽  
Vol 234 (2) ◽  
pp. 308-318 ◽  
Author(s):  
Zhu Yunfeng ◽  
Sun Yongrong ◽  
Zhao Wei ◽  
Wu Ling
Keyword(s):  
Navigation System ◽  
Estimation Algorithm ◽  
Formation Flight ◽  
Fusion Center ◽  
Relative Navigation ◽  
Data Link ◽  
Performance Simulation ◽  
Relative State ◽  
Navigation Algorithm ◽  
Navigation Information

For higher accuracy and better performance, a novel relative navigation framework named full parallel distributed architecture is presented, using inertial navigation system, global positioning system, and data link. Aiming at multiple aircraft, it is designed to enable each plane to serve as a fusion center. Also this structure enhances the collaboration between aircraft by sharing the relative navigation information. It breaks the limitation of the single fusion center method and can adapt to the reconfiguration of formation. A two-stage filtering estimation algorithm based on Kalman filter is developed to determine relative position, attitude, and velocity between the formation aircraft. Each vehicle contains not only a local filter but also a relative state filter, which helps to improve the accuracy of the relative state error model. The relative navigation system is designed as a closed loop system with parallel processing and real-time performance. Simulation results compared with the traditional centralized filtering method indicate that the approach provides better estimates and restrains the error divergency effectively.

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