Nowadays,flying ad hoc network(FANET)has captured great attention for its huge potential in military and civilian applications.However,the high-speed movement of unmanned aerial vehi-cles(UAVs)in three-dimensional(3D)...Nowadays,flying ad hoc network(FANET)has captured great attention for its huge potential in military and civilian applications.However,the high-speed movement of unmanned aerial vehi-cles(UAVs)in three-dimensional(3D)space leads to fast topology change in FANET and brings new challenges to traditional routing mechanisms.To improve the performance of packet trans-mission in the 3D high dynamic FANETs,we propose a 3D greedy perimeter stateless routing(GPSR)algorithm using adaptive Kalman prediction for FANETs with omnidirectional antenna(KOGPSR).Especially,in data forwarding part of the KOGPSR,we propose a new link metric for greedy forwarding based on a torus-shaped radiation pattern of the omnidirectional antenna of UAVs,and a restricted flooding strategy is introduced to solve the 3D void node problem in geographic routing.In addition,in order to enhance the accuracy of the location information of high dynamic UAVs,we design an adaptive Kalman algorithm to track and predict the motion of UAVs.Finally,a FANET simulation platform based on OPNET is built to depict the performance of the KOGPSR algorithm.The simulation results show that the proposed KOGPSR algorithm is more suitable for the actual 3D high dynamic FANET.展开更多
The difficulty of multiple targets tracking is how to quickly fulfill the target matching from one flame image to another and fix the position of the target. In order to accurately choose target feature information fo...The difficulty of multiple targets tracking is how to quickly fulfill the target matching from one flame image to another and fix the position of the target. In order to accurately choose target feature information for reliable matching, simplify operations under the reliable precondition, and realize precise moving objects tracking, an approach based on Kalman prediction and feature matching was proposed. The position of the target in next frame image was predicted by Kalman, and then the moving objects of two adjacent frames were matched by the centroid and area methods. When occlusion occurs, the best matching result was found to realize tracking by matching matrix algorithm. The simulation results show that the proposed method can achieve multiple targets tracking accurately and in real-time under complicated motion movements.展开更多
Focusing on the failure under the condition of target blocking, the similarity between target color and background color for the Camshift algorithm, an improved algorithm based on Camshift algorithm is proposed. Gauss...Focusing on the failure under the condition of target blocking, the similarity between target color and background color for the Camshift algorithm, an improved algorithm based on Camshift algorithm is proposed. Gaussian mixture model is used to determine the tracking area fast and accurately because it is not sensitive to the external conditions such as light and shadow. Kalman predictor is used to predict the blocked target effectively. The video is processed in the MATLAB environment. The moving target can be tracked and its position can be predicted accurately with the proposed improved algorithm. The results verify the feasibility and effectiveness of the algorithm.展开更多
The traditional oriented FAST and rotated BRIEF（ORB） algorithm has problems of instability and repetition of keypoints and it does not possess scale invariance. In order to deal with these drawbacks, a modified ORB...The traditional oriented FAST and rotated BRIEF（ORB） algorithm has problems of instability and repetition of keypoints and it does not possess scale invariance. In order to deal with these drawbacks, a modified ORB（MORB） algorithm is proposed. In order to improve the precision of matching and tracking, this paper puts forward an MOK algorithm that fuses MORB and Kanade-Lucas-Tomasi（KLT）. By using Kalman, the object＇s state in the next frame is predicted in order to reduce the size of search window and improve the real-time performance of object tracking. The experimental results show that the MOK algorithm can accurately track objects with deformation or with background clutters, exhibiting higher robustness and accuracy on diverse datasets. Also, the MOK algorithm has a good real-time performance with the average frame rate reaching 90.8 fps.展开更多
Airframe maintenance is traditionally performed at scheduled maintenance stops.The decision to repair a fuselage panel is based on a fixed crack size threshold,which allows to ensure the aircraft safety until the next...Airframe maintenance is traditionally performed at scheduled maintenance stops.The decision to repair a fuselage panel is based on a fixed crack size threshold,which allows to ensure the aircraft safety until the next scheduled maintenance stop.With progress in sensor technology and data processing techniques,structural health monitoring（SHM） systems are increasingly being considered in the aviation industry.SHM systems track the aircraft health state continuously,leading to the possibility of planning maintenance based on an actual state of aircraft rather than on a fixed schedule.This paper builds upon a model-based prognostics framework that the authors developed in their previous work,which couples the Extended Kalman filter（EKF） with a firstorder perturbation（FOP） method.By using the information given by this prognostics method,a novel cost driven predictive maintenance（CDPM） policy is proposed,which ensures the aircraft safety while minimizing the maintenance cost.The proposed policy is formally derived based on the trade-off between probabilities of occurrence of scheduled and unscheduled maintenance.A numerical case study simulating the maintenance process of an entire fleet of aircrafts is implemented.Under the condition of assuring the same safety level,the CDPM is compared in terms of cost with two other maintenance policies：scheduled maintenance and threshold based SHM maintenance.The comparison results show CDPM could lead to significant cost savings.展开更多
基金supported in part by the Shaanxi Provincial Key Research and Development Programs(2022ZDLGY05-04,2022ZDLGY05-03,2023-ZDLGY-33,2021ZDLGY04-08)。
文摘Nowadays,flying ad hoc network(FANET)has captured great attention for its huge potential in military and civilian applications.However,the high-speed movement of unmanned aerial vehi-cles(UAVs)in three-dimensional(3D)space leads to fast topology change in FANET and brings new challenges to traditional routing mechanisms.To improve the performance of packet trans-mission in the 3D high dynamic FANETs,we propose a 3D greedy perimeter stateless routing(GPSR)algorithm using adaptive Kalman prediction for FANETs with omnidirectional antenna(KOGPSR).Especially,in data forwarding part of the KOGPSR,we propose a new link metric for greedy forwarding based on a torus-shaped radiation pattern of the omnidirectional antenna of UAVs,and a restricted flooding strategy is introduced to solve the 3D void node problem in geographic routing.In addition,in order to enhance the accuracy of the location information of high dynamic UAVs,we design an adaptive Kalman algorithm to track and predict the motion of UAVs.Finally,a FANET simulation platform based on OPNET is built to depict the performance of the KOGPSR algorithm.The simulation results show that the proposed KOGPSR algorithm is more suitable for the actual 3D high dynamic FANET.
基金Project(61172089) supported by the National Natural Science Foundation of China
文摘The difficulty of multiple targets tracking is how to quickly fulfill the target matching from one flame image to another and fix the position of the target. In order to accurately choose target feature information for reliable matching, simplify operations under the reliable precondition, and realize precise moving objects tracking, an approach based on Kalman prediction and feature matching was proposed. The position of the target in next frame image was predicted by Kalman, and then the moving objects of two adjacent frames were matched by the centroid and area methods. When occlusion occurs, the best matching result was found to realize tracking by matching matrix algorithm. The simulation results show that the proposed method can achieve multiple targets tracking accurately and in real-time under complicated motion movements.
文摘Focusing on the failure under the condition of target blocking, the similarity between target color and background color for the Camshift algorithm, an improved algorithm based on Camshift algorithm is proposed. Gaussian mixture model is used to determine the tracking area fast and accurately because it is not sensitive to the external conditions such as light and shadow. Kalman predictor is used to predict the blocked target effectively. The video is processed in the MATLAB environment. The moving target can be tracked and its position can be predicted accurately with the proposed improved algorithm. The results verify the feasibility and effectiveness of the algorithm.
基金supported by the National Natural Science Foundation of China(61471194)the Fundamental Research Funds for the Central Universities+2 种基金the Science and Technology on Avionics Integration Laboratory and Aeronautical Science Foundation of China(20155552050)the CASC(China Aerospace Science and Technology Corporation) Aerospace Science and Technology Innovation Foundation Projectthe Nanjing University of Aeronautics And Astronautics Graduate School Innovation Base(Laboratory)Open Foundation Program(kfjj20151505)
文摘The traditional oriented FAST and rotated BRIEF（ORB） algorithm has problems of instability and repetition of keypoints and it does not possess scale invariance. In order to deal with these drawbacks, a modified ORB（MORB） algorithm is proposed. In order to improve the precision of matching and tracking, this paper puts forward an MOK algorithm that fuses MORB and Kanade-Lucas-Tomasi（KLT）. By using Kalman, the object＇s state in the next frame is predicted in order to reduce the size of search window and improve the real-time performance of object tracking. The experimental results show that the MOK algorithm can accurately track objects with deformation or with background clutters, exhibiting higher robustness and accuracy on diverse datasets. Also, the MOK algorithm has a good real-time performance with the average frame rate reaching 90.8 fps.
基金supported by UT-INSA Program(2013)the support of the China Scholarship Council(CSC)
文摘Airframe maintenance is traditionally performed at scheduled maintenance stops.The decision to repair a fuselage panel is based on a fixed crack size threshold,which allows to ensure the aircraft safety until the next scheduled maintenance stop.With progress in sensor technology and data processing techniques,structural health monitoring（SHM） systems are increasingly being considered in the aviation industry.SHM systems track the aircraft health state continuously,leading to the possibility of planning maintenance based on an actual state of aircraft rather than on a fixed schedule.This paper builds upon a model-based prognostics framework that the authors developed in their previous work,which couples the Extended Kalman filter（EKF） with a firstorder perturbation（FOP） method.By using the information given by this prognostics method,a novel cost driven predictive maintenance（CDPM） policy is proposed,which ensures the aircraft safety while minimizing the maintenance cost.The proposed policy is formally derived based on the trade-off between probabilities of occurrence of scheduled and unscheduled maintenance.A numerical case study simulating the maintenance process of an entire fleet of aircrafts is implemented.Under the condition of assuring the same safety level,the CDPM is compared in terms of cost with two other maintenance policies：scheduled maintenance and threshold based SHM maintenance.The comparison results show CDPM could lead to significant cost savings.
