Air Fore Engineering University

Fengcheng, China

Air Fore Engineering University

Fengcheng, China
Time filter
Source Type

Wang S.-L.,Air Fore Engineering University | Wei R.-X.,Air Fore Engineering University | Shen D.,Air Fore Engineering University | Qi X.-M.,Air Fore Engineering University | Luo P.,Unit 94691 of the PLA
Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | Year: 2013

The Voronoi diagram is a graph-based commonly used technique for creating the initial feasible path sets of an unmanned aerial vehicle (UAV), whose edges are the perpendicular bisector of the two closest threat sites. It does not take the threats' effective range into consideration, thus certain paths may go through some of the threat zones. To overcome the drawback of the Voronoi diagram, an important structure in computation geometry, Laguerre diagram, is introduced. It is proved that the generated initial paths will fall inside the interspaces of two closest threat zones when they do not intersect. Since the construction algorithm is difficult to implement, a new approach to build the Laguerre diagram based on the Delaunay graph is developed, whose time complexity is O(nlg n). Simulation results demonstrate the validity of the Laguerre diagram for path planning, and verify that the runtime of the construction algorithm can fulfill the requirement of on-line planning.

Zhao H.,Air Fore Engineering University | Zhou H.,Air Fore Engineering University | Weng X.-W.,Air Fore Engineering University | Li M.-D.,Air Fore Engineering University
Kongzhi yu Juece/Control and Decision | Year: 2015

In order to improve low filtering precision and divergence caused by sensor faults in target tracking, an adaptive unscented Kalman filter (UKF) is proposed. In the filtering process, by applying an adaptive matrix gene for the UKF according to the adaptive estimation principle, the algorithm can adjust the covariance matrixes of the state vector and innovation vector in real time, which meets the optimal conditions of the UKF algorithm. Then, the filtering divergence is judged and restrained by taking some measures. Compared with the traditional and existing adaptive UKF algorithm, the filter accuracy and numerical stability are remarkably improved in this adaptive UKF filter algorithm, and an adaptive capability to deal with sensor faults is performed. Simulation results show the effectiveness of the proposed algorithm. ©, 2015, Northeast University. All right reserved.

Li J.,Air Fore Engineering University | Li J.,No 93764 Unit | Feng C.,Air Fore Engineering University | Sun H.,No 93764 Unit | He S.,Air Fore Engineering University
Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica | Year: 2016

Aiming at the complexity of recognition and resolution on ballistic mid-course target, a method for three-dimensional reconstruction of ballistic target based on hybrid-scheme radar network combined low-resolution radar with high-resolution radar is proposed. Based on the separable model of nonlinear signal parameter, the amplitude-phase parameters of each scattering center on the ballistic target group with empennages are calculated by nonlinear least squares estimation method. Combined with the relationship of micro-motion features between radars, various scattering centers are separated by association processing between scattering centers. Ultimately, the three-Dimensional micro-motion features and the three-Dimensional position vectors are reconstructed by utilizing both the micro-Doppler characteristics and the relative position relation of each scattering center of ballistic target, and then the precession feature and structural parameters are estimated. Simulation results validate that the reconstruction precision of three-dimensional features has been maintained at about 92% when the signal noise ratio (SNR) is 5 dB. © 2016, Press of Chinese Journal of Aeronautics. All right reserved.

Wang S.-L.,Air Fore Engineering University | Wei R.-X.,Air Fore Engineering University | Guan X.-N.,Air Fore Engineering University
Kongzhi yu Juece/Control and Decision | Year: 2014

The mixing operation which is a key component in interacting multiple model(IMM) filter yields a non-Gaussian probability density function(PDF), IMM approximates the PDF of mixed random variable by a single Gaussian, the estimated covariance matrix is much large than the real covariance. As the mixing probability is time-varying, the mixing operation can be described as a nonlinear function, then the cubature rule in cubature Kalman filter(CKF) can be used to compute probability density function(PDF) of the mixture, that algorithm is called cubature rule aided interacting multiple model(CRIMM) filter. The accuracy of the resulting mean and covariance are analyzed by Taylor expansion. Simulation results show the CR-IMM performs better than IMM when the measurement becomes less accurate.

Wang S.,Air Fore Engineering University | Wei R.,Air Fore Engineering University | Guo Q.,Air Fore Engineering University | Wei W.,Air Fore Command College
Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica | Year: 2014

A lateral and longitudinal guidance law of unmanned aerial vehicles (UAVs) for coordinated standoff target tracking is proposed. The reference point guidance (RPG) is modified as the lateral guidance law of the UAV, and the convergence process of the relative distance between the UAV and the target is modeled by nonlinear differential equations. The asymptotic stability of the modified RPG is demonstrated based on this nonlinear system, and then the relationship between the RPG parameter and system performance is derived as the basis for parameter selection. Finally, a longitudinal guidance law is provided, and its asymptotic stability is demonstrated. According to simulations, the tracking error and integrated time absolute error (ITAE) of the modified RPG are smaller than those obtained from Lyapunov vector field guidance (LVFG) and model-based predictive control (MPC). Thus the modified RPG possesses faster response speed and higher steady state accuracy than LVFG and MPC.

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