This paper aims to present a multiple-model adaptive estimator (MMAE) to calibrate the star sensor low frequency error (LFE). The star sensor LFE, which is caused primarily by the…
Abstract
Purpose
This paper aims to present a multiple-model adaptive estimator (MMAE) to calibrate the star sensor low frequency error (LFE). The star sensor LFE, which is caused primarily by the periodic thermal distortion, has a great impact on spacecraft attitude determination accuracy.
Design/methodology/approach
The unfavorable effect of the LFE can be partly eliminated by using the calibration algorithm based on the augmented Kalman filter (AKF). However, the AKF may be worse than the traditional Kalman filter (KF) in the absence of the LFE. To cope with this problem, the MMAE is applied first time for combining the AKF and the KF in the spacecraft attitude determination system, such that satisfactory performance can be achieved in different operating scenarios.
Findings
The convergence of the presented MMAE is demonstrated through a formal derivation. A novel method is proposed to tune the MMAE design parameter, such that the convergence rate of the estimator is increased. It is shown via numerical studies that the presented algorithm outperforms the AKF and the KF.
Practical implications
The calibration algorithm is applicable for spacecraft attitude determination.
Originality/value
An effective star sensor LFE calibration algorithm based on the MMAE is developed. In addition, a novel method is proposed to increase convergence rate of the estimator.
Details
Keywords
The successful use of the standard extended Kalman filter (EKF) is restricted by the requirement on the statistics information of the measurement noise. The covariance of the…
Abstract
Purpose
The successful use of the standard extended Kalman filter (EKF) is restricted by the requirement on the statistics information of the measurement noise. The covariance of the measurement noise may deviate from its nominal value in practical environment, and the filtering performance may decline because of the statistical uncertainty. Although the adaptive EKF (AEKF) is available for recursive covariance estimation, it is often less accurate than the EKF with accurate noise statistics.
Design/methodology/approach
Aiming at this problem, this paper develops a parallel adaptive EKF (PAEKF) by combining the EKF and the AEKF with an adaptive law, such that the final state estimate is dominated by the EKF when the prior noise covariance is accurate, while the AEKF is activated when the actual noise covariance deviates from its nominal value.
Findings
The PAEKF can reduce the sensitivity of the algorithm to the model uncertainty and ensure the estimation accuracy in the normal case. The simulation results demonstrate that the PAEKF has the advantage of both the AEKF and the EKF.
Practical implications
The presented algorithm is applicable for spacecraft relative attitude and position estimation.
Originality/value
The PAEKF is presented for a kind of nonlinear uncertain systems. Stability analysis is provided to show that the error of the estimator is bounded under certain assumptions.
Details
Keywords
Kai Xiong, Chunling Wei and Peng Zhou
This paper aims to improve the performance of the autonomous optical navigation using relativistic perturbation of starlight, which is a promising technique for future space…
Abstract
Purpose
This paper aims to improve the performance of the autonomous optical navigation using relativistic perturbation of starlight, which is a promising technique for future space missions. Through measuring the change in inter-star angle due to the stellar aberration and the gravitational deflection of light with space-based optical instruments, the position and velocity vectors of the spacecraft can be estimated iteratively.
Design/methodology/approach
To enhance the navigation performance, an integrated optical navigation (ION) method based on the fusion of both the inter-star angle and the inter-satellite line-of-sight measurements is presented. A Q-learning extended Kalman filter (QLEKF) is designed to optimize the state estimate.
Findings
Simulations illustrate that the integrated optical navigation outperforms the existing method using only inter-star angle measurement. Moreover, the QLEKF is superior to the traditional extended Kalman filter in navigation accuracy.
Originality/value
A novel ION method is presented, and an effective QLEKF algorithm is designed for information fusion.
Details
Keywords
Kai Xiong, Chunling Wei and Liangdong Liu
The purpose of this paper is to present a variable structure multiple model adaptive estimator (VSMMAE) for liaison navigation system. Liaison navigation is an autonomous…
Abstract
Purpose
The purpose of this paper is to present a variable structure multiple model adaptive estimator (VSMMAE) for liaison navigation system. Liaison navigation is an autonomous navigation method where inter-satellite range measurements are used to estimate the orbits of all participating spacecrafts simultaneously.
Design/methodology/approach
To overcome the problem caused by an inaccurate initial state, a navigation algorithm is designed based on the multiple model adaptive estimation technique. The multiple models are constructed by different initial error covariance matrices. To reduce the computational cost, the likely-model set (LMS) algorithm is adopted to eliminate the unlikely models.
Findings
It is specified that the performance of the liaison navigation based on the extended Kalman filter (EKF) is sensitive to the initial error. Simulation results show that the VSMMAE outperforms the EKF in the presence of a large initial error.
Practical implications
The presented algorithm is applicable to spacecraft autonomous navigation.
Originality/value
A novel navigation algorithm based on the VSMMAE is developed. It is an effective method for the liaison navigation system.
Details
Keywords
The aim of the paper is to shed light on the use of chitosans and chitooligosaccharides as biopreservatives in various foods animal. Foods of animal and aquatic origin (milk…
Abstract
Purpose
The aim of the paper is to shed light on the use of chitosans and chitooligosaccharides as biopreservatives in various foods animal. Foods of animal and aquatic origin (milk, meat, fish, eggs, sea foods, etc) become contaminated with a wide range of microorganisms (bacteria, molds and yeasts) during harvesting, transporting, processing, handling and storage operations. Due to the perishable nature of these foods, their preservation is of utmost importance. Though many synthetic chemicals are available, yet their use is quite restricted due to their hazardous effects on human health.
Design/methodology/approach
Within the domain of food industry, traditionally chitosan is used for biopreservation of foods, which is well known for its nutritional and medicinal properties in human nutrition. However, chitooligosaccharides also possess a number of nutraceutical and health promoting properties in addition to their preservative effect and shelf-life extension of foods. In this study, the comparative effects of both chitosan and chitooligosaccharides on preservation of foods of animal and aquatic origin have been summarized.
Findings
Though chitosan has been extensively studied in various foods, yet the use of chitooligosaccharides has been relatively less explored. Chitooligosaccharides are bioactive molecules generated from chitosan and have several advantages over the traditional use of chitosan both in food products and on human health. But unfortunately, little or no literature is available on the use of chitooligosaccharides for preservation of some of the foods of animal origin. Notable examples in this category include cheese, beef, pork, chicken, fish, sea foods, etc.
Originality/value
This paper focuses on the effects of chitosans and chitooligosaccharides on the processing and storage quality of foods of animal and aquatic origin, which offers a promising future for the development of functional foods.
Details
Keywords
Wenhao Yu, Jun Li, Li-Ming Peng, Xiong Xiong, Kai Yang and Hong Wang
The purpose of this paper is to design a unified operational design domain (ODD) monitoring framework for mitigating Safety of the Intended Functionality (SOTIF) risks triggered…
Abstract
Purpose
The purpose of this paper is to design a unified operational design domain (ODD) monitoring framework for mitigating Safety of the Intended Functionality (SOTIF) risks triggered by vehicles exceeding ODD boundaries in complex traffic scenarios.
Design/methodology/approach
A unified model of ODD monitoring is constructed, which consists of three modules: weather condition monitoring for unusual weather conditions, such as rain, snow and fog; vehicle behavior monitoring for abnormal vehicle behavior, such as traffic rule violations; and road condition monitoring for abnormal road conditions, such as road defects, unexpected obstacles and slippery roads. Additionally, the applications of the proposed unified ODD monitoring framework are demonstrated. The practicability and effectiveness of the proposed unified ODD monitoring framework for mitigating SOTIF risk are verified in the applications.
Findings
First, the application of weather condition monitoring demonstrates that the autonomous vehicle can make a safe decision based on the performance degradation of Lidar on rainy days using the proposed monitoring framework. Second, the application of vehicle behavior monitoring demonstrates that the autonomous vehicle can properly adhere to traffic rules using the proposed monitoring framework. Third, the application of road condition monitoring demonstrates that the proposed unified ODD monitoring framework enables the ego vehicle to successfully monitor and avoid road defects.
Originality/value
The value of this paper is that the proposed unified ODD monitoring framework establishes a new foundation for monitoring and mitigating SOTIF risks in complex traffic environments.
Details
Keywords
Li Na, Xiong Zhiyong, Deng Tianqi and Ren Kai
The precise segmentation of brain tumors is the most important and crucial step in their diagnosis and treatment. Due to the presence of noise, uneven gray levels, blurred…
Abstract
Purpose
The precise segmentation of brain tumors is the most important and crucial step in their diagnosis and treatment. Due to the presence of noise, uneven gray levels, blurred boundaries and edema around the brain tumor region, the brain tumor image has indistinct features in the tumor region, which pose a problem for diagnostics. The paper aims to discuss these issues.
Design/methodology/approach
In this paper, the authors propose an original solution for segmentation using Tamura Texture and ensemble Support Vector Machine (SVM) structure. In the proposed technique, 124 features of each voxel are extracted, including Tamura texture features and grayscale features. Then, these features are ranked using the SVM-Recursive Feature Elimination method, which is also adopted to optimize the parameters of the Radial Basis Function kernel of SVMs. Finally, the bagging random sampling method is utilized to construct the ensemble SVM classifier based on a weighted voting mechanism to classify the types of voxel.
Findings
The experiments are conducted over a sample data set to be called BraTS2015. The experiments demonstrate that Tamura texture is very useful in the segmentation of brain tumors, especially the feature of line-likeness. The superior performance of the proposed ensemble SVM classifier is demonstrated by comparison with single SVM classifiers as well as other methods.
Originality/value
The authors propose an original solution for segmentation using Tamura Texture and ensemble SVM structure.
Details
Keywords
Hui Wang, Zheng Zhang, Zhao Xiong, Tianye Liu, Kai Long, Xusong Quan and Xiaodong Yuan
It is a huge technical and engineering challenge to realize the precise assembly of thousands of large optics in high power solid-state laser system. Using the 400-mm…
Abstract
Purpose
It is a huge technical and engineering challenge to realize the precise assembly of thousands of large optics in high power solid-state laser system. Using the 400-mm aperture-sized transport mirror as a case, this paper aims to present an intelligent numerical computation methodology for mounting performance analysis and modeling of large optics in a high-power laser system for inertial confinement fusion (ICF).
Design/methodology/approach
Fundamental principles of modeling and analysis of the transport mirror surface distortion are proposed, and a genetic algorithm-based computation framework is proposed to evaluate and optimize the assembly and mounting performance of large laser optics.
Findings
The stringent specifications of large ICF optics place very tight constraints upon the transport mirror’s assembly and mounts. The operational requirements on surface distortion [peak-to-valley and root mean square (RMS)] can be met as it is appropriately assembled by the close loop of assembly-inspection-optimization-fastening. In the end, the experimental study validates the reliability and effectiveness of the transport mirror mounting method.
Originality/value
In the assembly design and mounting performance evaluation of large laser optics, the whole study has the advantages of accurate evaluation and intelligent optimization on nano-level optical surface distortion, which provides a fundamental methodology for precise assembly and mounting of large ICF optics.
Details
Keywords
Humanoid robot has similar shape and action characteristics as humans, and it can complete some basic tasks instead of humans without changing the human environment, which makes…
Abstract
Purpose
Humanoid robot has similar shape and action characteristics as humans, and it can complete some basic tasks instead of humans without changing the human environment, which makes humanoid robot become the best structure and help form for robot to provide services for human beings.
Design/methodology/approach
The mobile operation control of humanoid robot is generated by the walking movement of humanoid robot's feet, and the robot's hand and arm complete grasping and other operations together.
Findings
On the basis of humanoid robot, the integrated system of software and hardware based on the KM34Z256 humanoid robot is described first, and a series of kinematics discussion on its mobile operation is carried out.
Originality/value
The research based on this project shows that the target recognition and positioning method is not only accurate and of high energy but also can realize the mobile operation of humanoid robot.
Details
Keywords
Hong Yue, Kai Li, Haiwen Zhao and Yi Zhang
The purpose of this paper is to introduce structured light image processing technology into pipeline welding automation projects, and develop a vision‐based pipeline girth‐welding…
Abstract
Purpose
The purpose of this paper is to introduce structured light image processing technology into pipeline welding automation projects, and develop a vision‐based pipeline girth‐welding robot. The welding torch can accurately track the weld and complete the omni‐orientation welding automatically.
Design/methodology/approach
Weld image processing adopts the base theory including Laplacian of Gaussian filter, neighbourhood mean filter, largest variance threshold segmentation and morphologic, etc. obtains good effect of weld recognition.
Findings
The paper uses a vision sensor to achieve the weld character's recognition and extraction, directly control the robot tracking weld to complete automation welding. Compared with the existing pipeline welding devices, it does not need the lay orbit or plot tracking mark, which can shorten the assistant time to improve the productivity.
Practical implications
The research findings can satisfy the need of whole‐directional automation welding for large diameter transportation pipe's circular abutting weld. It fits for the automation welding for the long‐distance transportation pipe of petroleum, natural gas, and water.
Originality/value
Aiming at the character recognition and extract of V‐type weld, the method combining the neighbourhood mean filter algorithm with the largest variance threshold segmentation is proposed to obtain the quick weld image processing speed.