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Study on autonomous navigation based on pulsar timing model

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Science China(Physics,Mechanics & Astronomy) 2009年第2期52卷 303-309页

作者： li jianxun KE XiZheng School of Automation and Information Engineering Xi′an University of TechnologyXi’an 710048China

The basic principle of pulsar timing model was introduced, and the general relativistic corrections were analyzed when pulse time of arrival (TOA) was transferred to coordinate TOA at the Solar System Barycentre. Based on the shifting, an iterative method of autonomous position determination for spacecraft was developed. Accordingly, the linear form of the position offset equation was evolved. Using the initial estimated value of spacecraft’s position as the input of pulsar timing equation, through calculation of the offset between measured or transferred and predicted TOA, the position offset can be solved by Least Squares. At last, the main error sources including modeling error and parameters error were discussed.

关键词： X-ray pulsar pulsar timing model autonomous navigation TOA measurement

Practical compensation for nonlinear dynamic thrust measurement system

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Chinese Journal of Aeronautics 2015年第2期28卷 418-426页

作者： Chen lin Chen Jie li jianxun Department of Automation Shanghai Jiao Tong University Shanghai Institute of Space Propulsion Shanghai Academy of Spaceflight Technology

The real dynamic thrust measurement system usually tends to be nonlinear due to the complex characteristics of the rig, pipes connection, etc. For a real dynamic measuring system, the nonlinearity must be eliminated by some adequate methods. In this paper, a nonlinear model of dynamic thrust measurement system is established by using radial basis function neural network （RBF-NN）, where a novel multi-step force generator is designed to stimulate the nonlinearity of the system, and a practical compensation method for the measurement system using left inverse model is proposed. Left inverse model can be considered as a perfect dynamic compensation of the dynamic thrust measurement system, and in practice, it can be approximated by RBF-NN based on least mean square （LMS） algorithms. Different weights are set for producing the multi-step force, which is the ideal input signal of the nonlinear dynamic thrust measurement system. The validity of the compensation method depends on the engine＇s performance and the tolerance error 0.5%, which is commonly demanded in engineering. Results from simulations and experiments show that the practical compensation using left inverse model based on RBF-NN in dynamic thrust measuring system can yield high tracking accuracy than the conventional methods.

关键词： Digital compensation Dynamic thrust measure-ment system Identification Left inverse model Nonlinear model Radial basis function neuralnetwork

Distributed state estimation and data fusion in wireless sensor networks using multi-level quantized innovation

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Science China(Information Sciences) 2016年第2期59卷 217-231页

作者： Zhi ZHANG jianxun li liu liU Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China College of Telecommunications & Information Engineering Nanjing University of Posts and Telecommunications

Low energy consumption and limited power supply are significant factors for wireless sensor networks(WSNs); thus, distributed state estimation and data fusion with quantized innovation are explored. The universal features of practical WSNs are investigated, and a dynamic transmission strategy is introduced. Furthermore,quantization state estimation based on Bayesian theory is derived. Unlike previous algorithms suitable for processing scalar measurement, the proposed distributed data fusion algorithm is applicable to general vector measurement. Furthermore, the efficiency of the proposed dynamic transmission strategy is analyzed. It is concluded that the proposed algorithm is more efficient than previous methods, and its estimation accuracy comparable to that of the standard Kalman filtering, which is based on analog-amplitude vector measurement.

关键词： data fusion distributed state estimation target tracking Kalman filtering quantization wireless sensor networks

A generalized rough set-based information flling technique for failure analysis of thruster experimental data

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Chinese Journal of Aeronautics 2013年第5期26卷 1182-1194页

作者： Han Shan Zhu Qiang li jianxun Chen lin Department of Automation Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education of China

Interval-valued data and incomplete data are two key problems for failure analysis of thruster experimental data and have been basically solved by the proposed methods in this paper. Firstly, information data acquired from the simulation and evaluation system formed as intervalvalued information system （IIS） is classified by the interval similarity relation. Then, as an improvement of the classical rough set, a new kind of generalized information entropy called ＂H＇-information entropy＂ is suggested for the measurement of uncertainty and the classification ability of IIS. There is an innovative information filling technique using the properties of H＇-information entropy to replace missing data by some smaller estimation intervals. Finally, an improved method of failure analysis synthesized by the above achievements is presented to classify the thruster experimental data, complete the information, and extract the failure rules. The feasibility and advantage of this method is testified by an actual application of failure analysis, whose performance is evaluated by the quantification of E-condition entropy.

关键词： Data acquisition Data classification Failure analysis Information filling Rough set

Pattern recognitionbased method for radar antideceptive jamming

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Journal of Systems Engineering and Electronics 2005年第4期16卷 802-805页

作者： Ma Xiaoyan Qin Jiangmin li jianxun Air Force Radar Academy Wuhan 430019 P. R. China

In order to make the effective ECCM to the deceptive jamming, especially the angle deceptive jamming, this paper establishes a signal-processing model for anti-deceptive jamming firstly, in which two feature-extracting algorithms, i.e. the statistical algorithm and the neural network （NN） algorithm are presented, then uses the RBF NN as the classitier in the processing model. Finally the two algorithms are validated and compared through some simulations.

关键词： angle deceptive jamming anti-jamming pattern recognition feature extraction neural network.

Analysis of quantization noise and state estimation with quantized measurements

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控制理论与应用（英文版） 2011年第1期9卷 66-75页

作者： Xu, Jian li, jianxun Xu, Sheng Department of Automation Shanghai Jiao Tong University Shanghai 200240 China College of Mechanical Engineering Chongqing University Chongqing 400030 China

The approximate correction of the additive white noise model in quantized Kalman filter is investigated under certain conditions. The probability density function of the error of quantized measurements is analyzed theoretically and experimentally. The analysis is based on the probability theory and nonparametric density estimation technique, respectively. The approximator of probability density function of quantized measurement noise is given. The numerical results of nonparametric density estimation algorithm demonstrate that the theoretical conclusion is reasonable. Based on the analysis of quantization noise, a novel algorithm for state estimation with quantized measurements also is proposed. The algorithm is based on the least-squares estimator and unscented transform. By least-squares estimator, the effective information is extracted from the quantized measurements. Also, using the information to update the estimated state can give a better estimation under the influence of quantization. The root mean square error (RMSE) of the proposed algorithm is compared with the RMSE of the existing methods for a typical tracking scenario in wireless sensor networks systems. Simulations provide a strong evidence that this tracking algorithm could indeed give us a more precise estimated result.

关键词： Wireless sensor networks Quantized observations Nonparametric density estimation Least-squares method Unscented transform

Mechanism and Method of Testing Fracture Toughness and Impact Absorbed Energy of Ductile Metals by Spherical Indentation Tests

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Chinese Journal of Mechanical Engineering 2023年第5期36卷 156-173页

作者： jianxun li Tairui Zhang Shang Wang Jirui Cheng Weiqiang Wang Key Laboratory of High-efciency and Clean Mechanical Manufacture(Ministry of Education) National Demonstration Center for Experimental Mechanical Engineering Education(Shandong University)School of Mechanical EngineeringShandong UniversityJinan 250061China School of Mechanical Engineering Southeast UniversityNanjing 211189China College of Electromechanical Engineering Qingdao University of Science and TechnologyQingdao 266061China

To address the problem of conventional approaches for mechanical property determination requiring destructive sampling, which may be unsuitable for in-service structures, the authors proposed a method for determining the quasi-static fracture toughness and impact absorbed energy of ductile metals from spherical indentation tests (SITs). The stress status and damage mechanism of SIT, mode I fracture, Charpy impact tests, and related tests were frst investigated through fnite element (FE) calculations and scanning electron microscopy (SEM) observations, respectively. It was found that the damage mechanism of SITs is diferent from that of mode I fractures, while mode I fractures and Charpy impact tests share the same damage mechanism. Considering the diference between SIT and mode I fractures, uniaxial tension and pure shear were introduced to correlate SIT with mode I fractures. Based on this, the widely used critical indentation energy (CIE) model for fracture toughness determination using SITs was modifed. The quasi-static fracture toughness determined from the modifed CIE model was used to evaluate the impact absorbed energy using the dynamic fracture toughness and energy for crack initiation. The efectiveness of the newly proposed method was verifed through experiments on four types of steels: Q345R, SA508-3, 18MnMoNbR, and S30408.

关键词： Spherical indentation tests Fracture toughness CIE model Impact absorbed energy

State estimation with quantized innovations in wireless sensor networks: Gaussian mixture estimator and posterior Cramér–Rao lower bound

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Chinese Journal of Aeronautics 2015年第6期28卷 1735-1746页

作者： Zhang Zhi li jianxun liu liu liu Zhaolei Han Shan Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Nanjing Research Institute of Electronics Technology Engineering Research Center of Wideband Wireless Communication Technology Ministry of EducationNanjing University of Posts and Telecommunications

Since the features of low energy consumption and limited power supply are very impor- tant for wireless sensor networks （WSNs）, the problems of distributed state estimation with quan- tized innovations are investigated in this paper. In the first place, the assumptions of prior and posterior probability density function （PDF） with quantized innovations in the previous papers are analyzed. After that, an innovative Gaussian mixture estimator is proposed. On this basis, this paper presents a Gaussian mixture state estimation algorithm based on quantized innovations for WSNs. In order to evaluate and compare the performance of this kind of state estimation algo- rithms for WSNs, the posterior Cram6r-Rao lower bound （CRLB） with quantized innovations is put forward. Performance analysis and simulations show that the proposed Gaussian mixture state estimation algorithm is efficient than the others under the same number of quantization levels and the performance of these algorithms can be benchmarked by the theoretical lower bound.

关键词： Posterior Cramer-Rao lower bounds Quantiation State estimation Target tracking Wireless sensor network

Improved Deformable Part Model For Object Detection Based on Scale Invariant Feature Transform

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Improved Deformable Part Model For Object Detection Based on...