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Calibration Method for INS Based on Multiple Actuator Function
Yeong-Bin Seo,Haesung Yu,Myeong-Jong Yu 제어·로봇·시스템학회 2023 International Journal of Control, Automation, and Vol.21 No.1
This paper presents a calibration method based on a multiple actuator function (MAF) to improve the navigation performance of the inertial navigation system (INS). The navigation performance of the INS can be improved by utilizing a compensation function. Existing calibration methods model the compensation function based on calibration coefficients obtained by indirect calibration. In indirect calibration, the calibration coefficients are calculated using acceleration errors. However, errors such as random walks, white noise, and bias instability can affect the precision of the calculated calibration coefficients. These errors can degrade the accuracy of the calibration coefficients and the compensation function. To overcome these limitations, the proposed method models a compensation function based on the MAF. The accuracy of the compensation function is improved by the accurate actuator angle and actuator position of the MAF. Unlike indirect calibration, the precision of the MAF is improved exclusively by navigation performance. The accurate actuator angle is calculated by adopting gradient descent and Q-learning, and the accurate actuator position is calculated by adopting the Bhattacharyya coefficient. The accuracy and precision of the proposed calibration method is evaluated by static-state tests and vehicle tests. The results show that the proposed calibration method is a valid approach to improve the navigation performance of the INS.
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최은철(Euncheol Choi),이석호(Suk-Ho Lee),강문기(Moon Gi Kang) 한국방송·미디어공학회 2010 방송공학회논문지 Vol.15 No.2
Recently, mean shift tracking algorithms have been proposed which use the information of color histogram together with some spatial information provided by the kernel. In spite of their fast speed, the algorithms are suffer from an inherent instability problem which is due to the use of an isotropic kernel for spatiality and the use of the Bhattacharyya coefficient as a similarity function. In this paper, we analyze how the kernel and the Bhattacharyya coefficient can arouse the instability problem. Based on the analysis, we propose a novel tracking scheme that uses a new representation of the location of the target which is constrained by the color, the area, and the spatiality information of the target in a more stable way than the mean shift algorithm. With this representation, the target localization in the next frame can be achieved by one step computation, which makes the tracking stable, even in difficult situations such as low-rate-frame environment, and partial occlusion.
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Object Modeling with Color Arrangement for Region-Based Tracking
Dae-Hwan Kim,정승원,Suryanto,Seung-Jun Lee,Hyo-Kak Kim,고성제 한국전자통신연구원 2012 ETRI Journal Vol.34 No.3
In this paper, we propose a new color histogram model for object tracking. The proposed model incorporates the color arrangement of the target that encodes the relative spatial distribution of the colors inside the object. Using the color arrangement, we can determine which color bin is more reliable for tracking. Based on the proposed color histogram model, we derive a mean shift framework using a modified Bhattacharyya distance. In addition, we present a method of updating an object scale and a target model to cope with changes in the target appearance. Unlike conventional mean shift based methods, our algorithm produces satisfactory results even when the object being tracked shares similar colors with the background.
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