Time filter

Source Type

Wang L.,Harbin Engineering University | Wang L.,Shanghai JiaoTong University | Li G.-C.,Harbin Engineering University | Qiao X.-W.,Harbin Engineering University | And 3 more authors.
Zidonghua Xuebao/Acta Automatica Sinica | Year: 2012

In order to solve the state estimation problem of nonlinear systems without knowing prior noise statistical characteristics, an adaptive unscented Kalman filter (UKF) based on the maximum likelihood principle and expectation maximization algorithm is proposed in this paper. In our algorithm, the maximum likelihood principle is used to find a log likelihood function with noise statistical characteristics. Then, the problem of noise estimation turns out to be maximizing the mean of the log likelihood function, which can be achieved by using the expectation maximization algorithm. Finally, the adaptive UKF algorithm with a suboptimal and recurred noise statistical estimator can be obtained. The simulation analysis shows that the proposed adaptive UKF algorithm can overcome the problem of filtering accuracy declination of traditional UKF used in nonlinear filtering without knowing prior noise statistical characteristics and that the algorithm can estimate the noise statistical parameters online.


Wu B.,Harbin University of Science and Technology | Xu H.,Beijing Universal Information Application Development Center | Qiao X.-W.,Xian Aerospace Precision Electromechanical Institute
Dianji yu Kongzhi Xuebao/Electric Machines and Control | Year: 2012

Considering the sharply increased computation burden caused by the increasement of state dimension multiplication in Augmented unscented Kalman filter (AUKF), a state switch unscented Kalman filter (SUKF) algorithm whose process and measurement noise has no correlation was proposed. Via selecting different state variables in time update and measurement update stage, the state dimension of real-time filtering was reduced and the number of Sigma points selected decreased, so the filter computation was reduced and speed was improved. Aming at the quaternion normalization restrictions in attitude determination, a parameter-switching algorithm was proposed. Through switching the quaternion parameter and the modified rodriguez parameter (MRPs), the quaternion weighted meanand covariance singularity problems were solved. The SINS/CCD attitude simulation results show that: compared with the AUKF, the proposed algorithm estimation accuracy is about equal and the estimation time reduces approximately 1/3.


Dai J.,Lanzhou University of Technology | Fu B.,Lanzhou University of Technology | Yao X.,Lanzhou University of Technology | Dai Y.,Lanzhou University of Technology | And 2 more authors.
Qiangjiguang Yu Lizishu/High Power Laser and Particle Beams | Year: 2012

In order to improve the concentration efficiency and eliminate the optical aberration, the umbrella-shaped keel structure has been introduced into the deployable concentrator. The concentration performance of deployable solar paraboloid concentrator with concentration power of which working in the space environment has been investigated with the software and . Under the influence of film tension and solar wind, the maximum stress of umbrella fabric is , is which is much smaller than the threshold intensity of and keel materials. The maximum deformation of umbrella fabric is , radius of the spot size is , the geometric concentration ratio could achieve , which only reduced than the standard parabolic concentrator. The results reveal that the influence of film tension and solar wind on the working shape of concentrator has been offset to a large extent by the introduction of umbrella-shaped keel structure, which would eliminate wrinkle and enhance the umbrella-shaped keel concentrator abilities of deployable and stability, as well as the selected umbrella-shaped keel structure and materials are appropriate.


Li C.,Northwest University, China | Wang Z.,Northwest University, China | Ding C.,Xian Aerospace Precision Electromechanical Institute
Lecture Notes in Electrical Engineering | Year: 2014

In response to mechanical fault in feature extraction problem, this paper presents a Fisher discrimination sparse coding method. This method is achieved by optimizing an objective function that includes two steps. First, this objective function works well in denoising where signals need to be reconstructed. Second, another objective function is added to the sparse coding framework, the discrimination power of the Fisher discriminative methods with the reconstruction property, and the sparsity of the sparse representation that can deal with the fault signal which is corrupted. Finally, the feature is extracted. In rolling bearing fault classification experiments, the new method improves the accuracy of classification. © 2014 Springer-Verlag.


Liu Z.-W.,Chang'an University | Zhao X.-M.,Chang'an University | Wang J.-J.,Chang'an University | Gao T.,Chang'an University | Li S.-Y.,Xian Aerospace Precision Electromechanical Institute
Zhongguo Gonglu Xuebao/China Journal of Highway and Transport | Year: 2016

To solve segmentation inaccuracy problem of weak contrast vehicle target, combining the multiple instance learning approach, a segmentation algorithm for vehicle target under weak contrast was proposed based on the visual attention mechanism. Firstly, characteristics of luminance gradient and texture gradient based on the local area of training images were extracted, and then characteristic learning was carried out by adopting multiple instance learning approach to obtain saliency model with learning ability, therefore predicted saliency detection results of test images can be got. Secondly, a simplified weighted graph module was constructed by the results from last step. The traditional graph cut frame was further optimized. Finally, optimal segmentation state vector was calculated corresponding to the second smallest eigenvalue of the general characteristic system represented by graph cut cost function, and the vehicle target in test image was segmented accurately. The test results show that the algorithm combining supervised saliency detection with graph cut can learn a particular category of image purposefully, and the saliency detection model from learning has a strong adaptability. At the same time, the algorithm can effectively improve the precision and efficiency of the original graph cut method using the saliency detection results as the inputs of graph cut. When the target and the background have little difference and the indistinct transition of the border under weak contrast condition, good segmentation results of vehicle target can be obtained. The PRI mean value (0.899), together with the F index (0.70) of the presented algorithm is higher than those of other three graph cut algorithms, and most GCE values are relatively concentrated between 0.15 and 0.17, which shows a small error. © 2016, Editorial Department of China Journal of Highway and Transport. All right reserved.


Xie B.,Xian Aerospace Precision Electromechanical Institute | Jiang Y.-F.,Xian Aerospace Precision Electromechanical Institute | Yan G.-M.,Northwestern Polytechnical University | Ren H.-K.,Xian Aerospace Precision Electromechanical Institute
Zhongguo Guanxing Jishu Xuebao/Journal of Chinese Inertial Technology | Year: 2013

As heading drift error remains a problem in a standalone pedestrian navigation system(PNS) that uses low-cost inertial measurement unit(IMU), an algorithm for integrating shoe-mounted IMU with building plane was proposed, and a novel auxiliary particle filter which is more applicable in indoor navigation scenario was devised. A double-deck framework comprises Kalman filter(KF) and particle filter(PF) was introduced, in which the lower KF applies zero-updating measurement for drift correction. The upper PF computes the step-wise changes of IMU position and heading to use them as measurements, and a corresponding pedestrian movement model was constructed for fusing nonlinear map-matching technique. The proposed algorithm is verified through experimental data collected from a low-performance IMU mounted on foot: the final positioning error of 300 m travel distance is less than 0.3 m. It is also shown that the consistent positioning accuracy and reliability of a PNS could be improved effectively with the modified auxiliary particle filter.


Xie B.,Xian Aerospace Precision Electromechanical Institute | Jiang Y.-F.,Xian Aerospace Precision Electromechanical Institute | Yan G.-M.,Northwestern Polytechnical University | Chen Y.,Xian Aerospace Precision Electromechanical Institute
Zhongguo Guanxing Jishu Xuebao/Journal of Chinese Inertial Technology | Year: 2014

For the purpose of extending the application of inertia freezing methodology into moving-base fine-alignment and promoting computational efficiency, an indirect fine-alignment algorithm is presented which introduces earth-centered and earth-fixed (ECEF) frame as intermediate reference. The mathematical formulation of the inertial sensor/odometer integration system is given within ECEF frame, and the corresponding ψ-angle error model is outlined. By taking the SINS-vehicle misaligning angle and lever arm into account, the derivation of the appropriate Kalman filter (KF) is discussed. The proposed algorithm is verified through experimental data collected from six traveling routes. In comparison with geographic-frame KF algorithm, the ECEF-frame indirect approach has shorter stabilizing time and performs better in robustness, and a better overall accuracy of 1 mil (1σ) azimuth error within 600 s can be achieved. The ECEF- frame KF is less sensitive to changes of initialization parameters, which is useful for practical application. ©, 2014, Editorial Department of Journal of Chinese Inertial Technology. All right reserved.


Yang M.-X.,Xian Aerospace Precision Electromechanical Institute | Chen J.-J.,Xian Aerospace Precision Electromechanical Institute
Zhongguo Guanxing Jishu Xuebao/Journal of Chinese Inertial Technology | Year: 2010

This paper tries to use models to reduce the static temperature effects for FOGs working in slow temperature-variation environment. First, the main causes of FOG's static temperature effects are analyzed, and the experiment principle and its compensate method are given. Then the experiment schemes are designed and tested. The testing data shows that the bias and the scale factor of FOG are both approximately linear to the static temperature. From the 1st to 7th order models constructed by the least squares method, the third order model is selected and used to compensate the output of FOG. The comparison results show that the proposed method could significantly improve the precision of FOG in relatively stable temperature field, which is value in engineering for medium- and high-precision FOG.

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