Time filter

Source Type

Xiao Q.,Beihang University | Wu Y.,Army Aviation Research Institute | Fu H.,Beihang University | Zhang Y.,Beihang University
IET Signal Processing | Year: 2015

This paper proposed a two-stage robust extended Kalman filter (TREKF) for state estimation of non-linear uncertain system with unknown inputs. In engineering practice, the extended Kalman filter (EKF) with unknown inputs of the non-linear uncertain system may be degraded or even diverged. The optimal two-stage EKF (TEKF) is designed to solve the unknown inputs. The robust EKF (REKF) is considered to solve the non-linear uncertain system for a long time. However, the information about the non-linear uncertain system with unknown inputs is always incorrect. To solve this problem, the TREKF is designed by using the advantages of the TEKF and REKF, furthermore, its stability is proved. Finally, the performances of the TREKF, which are compared with the results of the REKF, TEKF and EKF, are verified by illustrating a numerical example of the powered descent phase of Mars EDL (entry, descent and landing). These also verify that the unfavourable effects of the model uncertainties and the unknown inputs are reduced efficiently by using the TREKF for the miniature coherent altimeter and velocimeter and inertial measurement unit integrated navigation during the powered descent phase of Mars EDL. © The Institution of Engineering and Technology 2015.

Wang W.-G.,Beijing Institute of Technology | Wang W.-G.,Ordnance Engineering College | Sun L.,Army Aviation Research Institute
Binggong Xuebao/Acta Armamentarii | Year: 2014

For gearbox fault feature extraction, a novel method based on ensemble empirical mode decomposition and Choi-Williams distribution for gearbox vibration signal extraction is proposed. Firstly, vibration data are decomposed into several intrinsic mode functions (IMF) with EEMD, and IMFs are sorted by kurtosis criterion, then CWD is applied to the selected IMF which kurtosis is larger than others, the Choi-Williams distribution features in time, frequency and amplitude domains of the original signal can be extracted. On the basis of discussing teeth break and crack vibration fault mechanism of gearbox, the proposed method is used to analyze the vibration signal of the actual fault gearbox. The result shows that this method can efficiently extract the fault information and have great importance for condition recognition and fault diagnosis of gearbox.

Fu H.,Beihang University | Yang Y.,Beihang University | Xiao Q.,Beihang University | Wu Y.,Army Aviation Research Institute | Zhang Y.,Beihang University
Advances in Space Research | Year: 2015

Accurate navigation systems are required for future pinpoint Mars landing missions. A radio ranging augmented inertial measurement unit (IMU) navigation system concept is considered for the guided atmospheric entry phase. The systematic errors associated to the radio ranging and inertial measurements, and the atmospheric mission uncertainties are considered to be unknown. This paper presents the extension of an unbiased minimum-variance (EUMV) filter of a radio beacon/IMU navigation system. In the presence of unknown dynamics inputs, the filter joins the system state and the unknown systematic error estimation of a stochastic nonlinear time-varying discrete system. 3-DOF simulation results show that the performances of the proposed navigation filter algorithm, 100 m estimated altitude error and 8 m/s estimated velocity error, fulfills the need of future pinpoint Mars landing missions. © 2014 COSPAR. Published by Elsevier Ltd. All rights reserved.

Liu Y.,National University of Defense Technology | Liu J.,National University of Defense Technology | Bai X.-Z.,Army Aviation Research Institute
Guofang Keji Daxue Xuebao/Journal of National University of Defense Technology | Year: 2011

A new uncoupled algorithm of simulating chemical non-equilibrium flow originally realized by finite difference method was extended to the unstructured finite volume method, which makes the simulation of reaction flow in complex configurations possible. The H 2/Air shock-induced oscillating combustion experiment conducted by Lehr was simulated, and the computed oscillating frequencies conformed well with the ones acquired by experiment, which indicates that the present method is temporally and spatially second order accurate. It is also demonstrated that geometrical configuration plays a definitive role in the combustion regime. If the truncated angle is less or equal to 15 degrees, high frequency oscillating combustion in regular regime occurs, while if the angle is larger or equal to 20 degrees, low frequency oscillating combustion in large-disturbance regime is observed.

Yang H.-Y.,Tsinghua University | You Z.,Tsinghua University | Wang L.,Army Aviation Research Institute
Huanan Ligong Daxue Xuebao/Journal of South China University of Technology (Natural Science) | Year: 2012

In the accurate tracking of multiple targets in clutter by using a collaborative network system with hierarchical and distributed information processing structure, both the measurement uncertainty and the sensor assignment to the target as well as the local fusion centers must be taken into consideration. In order to solve these problems, a dynamic sensor management method for distributed tracking is proposed. In this method, first, the criteria to evaluate the tracking performance are determined based on the solution to the modified Riccati difference equation, with which the objective function of the dynamic sensor management is constructed. Then, according to a hierarchical optimization strategy and by using the improved ant colony algorithm, an approximate optimal solution is obtained in real time. Finally, the optimal multi-target tracking trajectories are obtained by using a distributed fusion algorithm. Simulated results indicate that, as compared with the two dynamic sensor management methods, namely NN-Clustering and MV-Clustering, the proposed method is of higher multi-target tracking accuracy and higher utilization rate of network resource.

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