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Xiang Xu   Dr.  Graduate Student or Post Graduate 
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Xiang Xu published an article in January 2018.
Top co-authors
Yao Li

5 shared publications

Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology, Ministry of Education, Nanjing 210096, China;(X.X.);(T.Z.);(Y.L.)

Tao Zhang

2 shared publications

Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology, Ministry of Education, Nanjing 210096, China;(X.X.);(T.Z.);(Y.L.)

Jinwu Tong

1 shared publications

Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology, Nanjing 210096, China;(X.X.);(T.Z.);(Y.L.);(J.T.)

4
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14
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Distribution of Articles published per year 

Total number of journals
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2
 
Publications
Article 0 Reads 1 Citation A Coarse-Alignment Method Based on the Optimal-REQUEST Algorithm Yongyun Zhu, Tao Zhang, Xiang Xu Published: 16 January 2018
Sensors, doi: 10.3390/s18010239
DOI See at publisher website PubMed View at PubMed ABS Show/hide abstract
In this paper, we proposed a coarse-alignment method for strapdown inertial navigation systems based on attitude determination. The observation vectors, which can be obtained by inertial sensors, usually contain various types of noise, which affects the convergence rate and the accuracy of the coarse alignment. Given this drawback, we studied an attitude-determination method named optimal-REQUEST, which is an optimal method for attitude determination that is based on observation vectors. Compared to the traditional attitude-determination method, the filtering gain of the proposed method is tuned autonomously; thus, the convergence rate of the attitude determination is faster than in the traditional method. Within the proposed method, we developed an iterative method for determining the attitude quaternion. We carried out simulation and turntable tests, which we used to validate the proposed method’s performance. The experiment’s results showed that the convergence rate of the proposed optimal-REQUEST algorithm is faster and that the coarse alignment’s stability is higher. In summary, the proposed method has a high applicability to practical systems.
Article 0 Reads 3 Citations An IMM-Aided ZUPT Methodology for an INS/DVL Integrated Navigation System Yiqing Yao, Xiaosu Xu, Xiang Xu Published: 05 September 2017
Sensors, doi: 10.3390/s17092030
DOI See at publisher website PubMed View at PubMed ABS Show/hide abstract
Inertial navigation system (INS)/Doppler velocity log (DVL) integration is the most common navigation solution for underwater vehicles. Due to the complex underwater environment, the velocity information provided by DVL always contains some errors. To improve navigation accuracy, zero velocity update (ZUPT) technology is considered, which is an effective algorithm for land vehicles to mitigate the navigation error during the pure INS mode. However, in contrast to ground vehicles, the ZUPT solution cannot be used directly for underwater vehicles because of the existence of the water current. In order to leverage the strengths of the ZUPT method and the INS/DVL solution, an interactive multiple model (IMM)-aided ZUPT methodology for the INS/DVL-integrated underwater navigation system is proposed. Both the INS/DVL and INS/ZUPT models are constructed and operated in parallel, with weights calculated according to their innovations and innovation covariance matrices. Simulations are conducted to evaluate the proposed algorithm. The results indicate that the IMM-aided ZUPT solution outperforms both the INS/DVL solution and the INS/ZUPT solution in the underwater environment, which can properly distinguish between the ZUPT and non-ZUPT conditions. In addition, during DVL outage, the effectiveness of the proposed algorithm is also verified.
Article 4 Reads 0 Citations Spacecraft attitude estimation based on matrix Kalman filter and recursive cubature Kalman filter Tao Zhang, Xiang Xu, Zhicheng Wang Published: 08 August 2017
Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, doi: 10.1177/0954410017723359
DOI See at publisher website
Article 0 Reads 11 Citations A Kalman Filter for SINS Self-Alignment Based on Vector Observation Xiang Xu, Xiaosu Xu, Tao Zhang, Yao Li, Jinwu Tong, Gert F. ... Published: 29 January 2017
Sensors, doi: 10.3390/s17020264
DOI See at publisher website PubMed View at PubMed ABS Show/hide abstract
In this paper, a self-alignment method for strapdown inertial navigation systems based on the q-method is studied. In addition, an improved method based on integrating gravitational apparent motion to form apparent velocity is designed, which can reduce the random noises of the observation vectors. For further analysis, a novel self-alignment method using a Kalman filter based on adaptive filter technology is proposed, which transforms the self-alignment procedure into an attitude estimation using the observation vectors. In the proposed method, a linear psuedo-measurement equation is adopted by employing the transfer method between the quaternion and the observation vectors. Analysis and simulation indicate that the accuracy of the self-alignment is improved. Meanwhile, to improve the convergence rate of the proposed method, a new method based on parameter recognition and a reconstruction algorithm for apparent gravitation is devised, which can reduce the influence of the random noises of the observation vectors. Simulations and turntable tests are carried out, and the results indicate that the proposed method can acquire sound alignment results with lower standard variances, and can obtain higher alignment accuracy and a faster convergence rate.
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