Equality Constrained Robust Measurement Fusion for Adaptive Kalman-Filter-Based Heterogeneous Multi-Sensor Navigation

Zhou, Zebo; Li, Yong; Liu, Junning; Li, Gun

doi:10.1109/taes.2013.6621807

Cited by 59 publications

(6 citation statements)

References 25 publications

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“…The Kalman filter has the advantages of estimating and correcting the object motion state [37]. As an effective estimation algorithm, the Kalman filter is widely used in engineering applications such as radar and computer vision [38].…”

Section: Using Kalman Filter To Improve the Tracking Acc Uracymentioning

confidence: 99%

Attitude estimation of a permanent magnet spherical motor based on an improved fast discriminative scale space tracking algorithm

Xue

Wang

et al. 2020

Meas. Sci. Technol.

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A permanent magnet spherical motor (PMSM) can perform a three-degree-of-freedom operation. The estimation of the attitude of the rotor is one of the key steps for realizing the closed-loop control of PMSM. An attitude estimation method based on a target-tracking algorithm is proposed in this study. Firstly, a high-speed camera is used to capture a video sequence of the spherical motor in motion. The location of the target is obtained by introducing an improved fast discriminative scale space tracking (IFDSST) algorithm to track the video sequence. In consideration of the motor's output shaft being covered with load, the singletarget tracking algorithm is improved into a multi-target tracking algorithm. Markers, which are symmetrical with respect to the output shaft, are made on the surface of the rotor, and their attitudes are obtained from the images captured by the tracking algorithm. Secondly, the attitude of the output shaft is estimated by the coordinate transformation and the positional relationship between the markers and the output shaft. The effectiveness and superiority of the proposed algorithm are verified by comparing it with a micro-electromechanical system (MEMS) method and a fast -complementary filter (FCF) method. Three types of motor motions, including yaw, spin, and tilt, are tested in the experiments, and the average angle error or trajectory error of the proposed IFDSST method reduces around 33%, 53%, and 79% as compared with those of the MEMS and FCF methods, respectively. Experiments show that the proposed algorithm can effectively and accurately measure the attitude of the motor's rotor.

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Section: Using Kalman Filter To Improve the Tracking Acc Uracymentioning

confidence: 99%

Attitude estimation of a permanent magnet spherical motor based on an improved fast discriminative scale space tracking algorithm

Xue

Wang

et al. 2020

Meas. Sci. Technol.

View full text Add to dashboard Cite

show abstract

“…All of the measurements are guaranteed theoretically without loss [23]; however, this method increases the computational intensity of the central site, and is vulnerable to gross errors. Conversely, distributed data fusion requires a low communication bandwidth, because each sensor transmits processed data instead of raw data [4,24,25]. Thus, distributed data fusion has been used in numerous situations.…”

Section: Algorithm Descriptionmentioning

confidence: 99%

Real-Time Weighted Data Fusion Algorithm for Temperature Detection Based on Small-Range Sensor Network

Zhang

Nan

Wang

2018

Sensors

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Biological oxidation pretreatment, which can improve the yield of gold, is the main gold extraction technology for disposing refractory gold ore with high arsenic and sulfur. The temperature of the oxidation tank influences the oxidation efficiency between the ore pulp and bacteria, including the yield of gold. Therefore, measurement has consistently been an important subject for researchers. As an effective data processing method, data fusion has been used extensively in many fields of industrial production. However, the interference of equipment or external factors such as the diurnal temperature difference or powerful wind may constantly increase measurement errors and damage certain sensors, which may transmit error data. These problems can be solved by following a pretreatment process. First, we establish a heat transfer mechanism model. Second, we design a small-range sensor network for the pretreatment process and present a layered fusion structure of sharing sensors using a multi-connected fusion structure. Third, we introduce the idea of iterative operation in data processing. In addition, we use prior data for predicting state values twice in order to improve the effectiveness of extended Kalman filtering in one time step. This study also proposes multi-fading factors on the basis of a weighted fading memory index to adjust the prediction error covariance. Finally, the state estimation accuracy of each sensor can be used as a weighting principle for the predictive confidence of each sensor by adding a weighting factor. In this study, the performance of the proposed method is verified by simulation and compared with the traditional single-sensor method. Actual industrial measurement data are processed by the proposed method for the equipment experiment. The performance index of the simulation and the experiment shows that the proposed method has a higher global accuracy than the traditional single-sensor method. Simulation results show that the accuracy of the proposed method has a 55% improvement upon that of the traditional single-sensor method, on average. In the equipment experiment, the accuracy of the industrial measurement improved by 37% when using the proposed method.

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“…Zhou has proposed a new algorithm, the so-called constrained adaptive robust integration Kalman filter (CARIKF) is presented, which implements adaptive integration upon the robust direct fusion solution [16]. Wang has proposed the algorithms of the navigation data fusion and the obstacle avoidance [17]. As can be seen from the above analysis, according to different practical application scenarios, selecting different navigation sensors to build a multisource fusion navigation system is becoming an important way to improve the reliability and accuracy of the system.…”

Section: Introductionmentioning

confidence: 99%

Resilient Multi-Source Integrated Navigation Method for Aerospace Vehicles Based on On-Line Evaluation of Redundant Information

et al. 2022

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Aerospace vehicle navigation systems are equipped with multi-source redundant navigation sensors. According to the characteristics of the above navigation system configuration, building a resilient navigation framework to improve the accuracy and robustness of the navigation system has become an urgent problem to be solved. In the existing integrated navigation methods, redundant information is only used for backup. So, it cannot use the redundant navigation information to improve the accuracy of the navigation system. In this paper, a resilient multi-source fusion integrated navigation method based on comprehensive information evaluation has been proposed by combining of qualitative analysis and quantitative analysis in information theory. Firstly, this paper proposes a multi-layer evaluation framework of redundant information and carries out quantitative analysis of redundant information with the information disorder analysis theory to improve the reliability of the navigation system. Secondly, a navigation output effectiveness evaluation system has been established to analyze the output of heterogeneous navigation subsystems qualitatively to improve the fusion accuracy. Finally, through the mutual correction of multi-level information evaluation results, the error decoupling between the output parameters of heterogeneous navigation sensors has been realized to improve the robustness of the system. The experimental results show that the method proposed in this paper can adaptively allocate and adjust the weight of navigation information at all levels, realize the “non-stop” work of the navigation system and enhance the resilient of the navigation architecture. The navigation accuracy is improved compared with the existing multi-source fusion algorithm, which reflects the reliability and robustness of this algorithm.

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Equality Constrained Robust Measurement Fusion for Adaptive Kalman-Filter-Based Heterogeneous Multi-Sensor Navigation

Cited by 59 publications

References 25 publications

Attitude estimation of a permanent magnet spherical motor based on an improved fast discriminative scale space tracking algorithm

Attitude estimation of a permanent magnet spherical motor based on an improved fast discriminative scale space tracking algorithm

Real-Time Weighted Data Fusion Algorithm for Temperature Detection Based on Small-Range Sensor Network

Resilient Multi-Source Integrated Navigation Method for Aerospace Vehicles Based on On-Line Evaluation of Redundant Information

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