Four-dimensional descent trajectory optimization for aircraft in turbulence

Li, Chuang; Liu, Xiaoxiong; Qing-yuan, MA; Shen, Jian

doi:10.1109/icinfa.2016.7831920

Cited by 4 publications

(2 citation statements)

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“…Modern measurement methods include radars, high-speed cameras, airborne navigation and photoelectric theodolites. They can be filtered and estimated through target motion to obtain the final accurate position of the aircraft [1,2]. Solving the filtering problem, especially the filtering of manoeuvring targets, is an important part of the target tracking process and has been widely used in military and civilian fields such as aerospace and surveying [3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Aircraft trajectory filtering method based on Gaussian‐sum and maximum correntropy square‐root cubature Kalman filter

Bai

et al. 2022

Cognitive Comp and Systems

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Aiming at meetiing the need to filtering flight trajectory data for aircraft testing, a novel adaptive cubature Kalman filter (CKF) is proposed based on the maximum correntropy and Gaussian-sum in this paper. Firstly, based on the traditional CKF algorithm, we introduced a Gaussian-sum method to approximate non-Gaussian noise to get more accurate filtering results in view of the problem of reduced filtering accuracy caused by the inherent non-Gaussian nature of the noise and the system non-linearity. Secondly, the maximum correntropy criterion is introduced to solve further the problem of improving the filtering accuracy of the system in the case of non-linearity. Simulation results and actual data verification showed that the Square-root cubature Kalman filter algorithm based on the maximum correntropy and Gaussian-sum has higher accuracy than traditional filtering algorithms, which verified the algorithm's effectiveness in the application.

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Section: Introductionmentioning

confidence: 99%

Aircraft trajectory filtering method based on Gaussian‐sum and maximum correntropy square‐root cubature Kalman filter

Bai

et al. 2022

Cognitive Comp and Systems

View full text Add to dashboard Cite

show abstract

“…The map by Charles Joseph Minard, which portrays the losses suffered by Napoleon's army in the Russian campaign of 1812, probably is the most famous map-oriented trajectory visualization ever drawn [9] (Fig. Nowadays, map-oriented trajectory visualization has been extensively studied to not only support transportation management [10][11][12], but also contribute to solving urban-related problems including jam monitoring [13], route recommendation [14],…”

Section: Map Oriented Trajectory Visualizationmentioning

confidence: 99%