Optimal selection and adaptability analysis of matching area for terrain aided navigation

Chen, Rui; Zhang, Qieqie; Zhao, Long

doi:10.1049/rsn2.12158

Cited by 3 publications

(2 citation statements)

References 18 publications

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“…Terrain-aided navigation utilizes airborne terrain-elevation databases, barometric altimeters, and radio altimeters to achieve multi-sensor, non-redundant, and heterogeneous fusion navigation. Various TAN algorithms exist, and this paper primarily investigates the integrity monitoring method of the robust BITAN algorithm [30]. The BITAN algorithm encompasses two working modes: search and tracking.…”

Section: Non-redundant Navigation Source Tanmentioning

confidence: 99%

Two-Level Integrity-Monitoring Method for Multi-Source Information Fusion Navigation

Chen,

Zhao

2023

Remote Sensing

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To address the issue of integrity monitoring for a multi-source information fusion navigation system, a theoretical framework of two-level integrity monitoring is proposed. Firstly, at the system level, a system-integrity-monitoring method based on the Kalman filter weighted least-squares form is established to detect and isolate faulty navigation sources. Secondly, at the sensor level, considering the redundancy of the faulty navigation sources, this paper presents the design of a multi-mode comprehensive fault-detection method for non-redundant navigation sources. Additionally, an extended-dimension matrix optimized sensor-fault detection and verification method for redundant navigation sources is proposed. Finally, integrity risk allocation criteria are established based on the effectiveness of navigation sources to calculate the system protection level and trigger integrity alarms. The two-level integrity-monitoring method was tested on a multi-source information fusion navigation system integrated with an inertial navigation system (INS), global positioning system (GPS), BeiDou satellite navigation system (BDS), Doppler velocity log (DVL), barometric altimeter (BA), and terrain-aided navigation (TAN). Test results demonstrate that the proposed method can effectively isolate the faulty navigation source within 10 s. Furthermore, it can detect the faulty sensors within the faulty navigation sources, thereby enhancing the reliability and robustness of the multi-source information fusion navigation system.

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Section: Non-redundant Navigation Source Tanmentioning

confidence: 99%

Two-Level Integrity-Monitoring Method for Multi-Source Information Fusion Navigation

Chen,

Zhao

2023

Remote Sensing

Self Cite

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“…Among them, suitable-matching area selection is the first step in scene-matching navigation. It is the basis for reference image preparation and track planning and is also the key to correcting positioning and reducing yaw [13]. Since the matching performance of the reference image is closely related to the matching probability and accuracy, selecting the suitable-matching area will directly affect the overall performance of the navigation and positioning system.…”

Section: Introductionmentioning

confidence: 99%

Suitable-Matching Areas’ Selection Method Based on Multi-Level Saliency

Jiang,

Luo,

Liu

2023

Remote Sensing

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Scene-matching navigation is one of the essential technologies for achieving precise navigation in satellite-denied environments. Selecting suitable-matching areas is crucial for planning trajectory and reducing yaw. Most traditional selection methods of suitable-matching areas use hierarchical screening based on multiple feature indicators. However, these methods rarely consider the interrelationship between different feature indicators and use the same set of screening thresholds for different categories of images, which has poor versatility and can easily cause mis-selection and omission. To solve this problem, a suitable-matching areas’ selection method based on multi-level saliency is proposed. The matching performance score is obtained by fusing several segmentation levels’ salient feature extraction results and performing weighted calculations with the sub-image edge density. Compared with the hierarchical screening methods, the matching performance of the candidate areas selected by our algorithm is at least 22.2% higher, and it also has a better matching ability in different scene categories. In addition, the number of missed and wrong selections is significantly reduced. The average matching accuracy of the top three areas selected by our method reached 0.8549, 0.7993, and 0.7803, respectively, under the verification of multiple matching algorithms. Experimental results show this paper’s suitable-matching areas’ selection method is more robust.

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Ground collision avoidance system with multi-trajectory risk assessment and decision function

Chen,

Zhao

2024

Aeronaut. j.

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The traditional ground collision avoidance system (GCAS) makes avoidance decisions based on predicted collision time, without considering the impact of terrain environment and dynamic changes in load factor on avoidance decisions. This increases the risk of ground collisions for the aircraft. To solve the problem, a GCAS with multi-trajectory risk assessment and decision function is proposed. Firstly, a variety of predicted flight avoidance trajectories are established within the final manoeuvering capability of the aircraft. Secondly, for each predicted trajectory, the uncertain length between adjacent prediction points is used to construct a rectangular distance bin, and the terrain data below the avoided trajectory is extracted. Finally, the regret theory is used to establish a multi-attribute avoidance decision model to evaluate and prioritise the risk of collision avoidance trajectories, to provide effective collision avoidance decision for pilots. The algorithm is tested and verified with real digital elevation model and simulated flight data, and compared with traditional GCAS. Simulation results show that the proposed algorithm can comprehensively consider manoeuvering performance and threatening terrain, and provide safe and effective avoidance decisions for pilots.

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Optimal selection and adaptability analysis of matching area for terrain aided navigation

Cited by 3 publications

References 18 publications

Two-Level Integrity-Monitoring Method for Multi-Source Information Fusion Navigation

Two-Level Integrity-Monitoring Method for Multi-Source Information Fusion Navigation

Suitable-Matching Areas’ Selection Method Based on Multi-Level Saliency

Ground collision avoidance system with multi-trajectory risk assessment and decision function

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