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	A Gaussian mixture regression model based adaptive filter for non-Gaussian noise without a priori statistic 期刊论文 OAI收割 SIGNAL PROCESSING, 2022, 卷号: 190, 页码: 13 作者: Cui, Haoran; Wang, Xiaoxu; Gao, Shuaihe; Li, Tiancheng \| 收藏 \| 浏览/下载：36/0 \| 提交时间：2021/11/26 Nonlinear adaptive filter Unknown and non-Gaussian noises Variational Bayesian Gaussian mixture model
	The new approach for infrared target tracking based on the particle filter algorithm (EI CONFERENCE) 会议论文 OAI收割 International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications, May 24, 2011 - May 24, 2011, Beijing, China 作者: Sun H.; Han H.-X.; Sun H. 收藏 \| 浏览/下载：60/0 \| 提交时间：2013/03/25 Target tracking on the complex background in the infrared image sequence is hot research field. It provides the important basis in some fields such as video monitoring precision and video compression human-computer interaction. As a typical algorithms in the target tracking framework based on filtering and data connection the particle filter with non-parameter estimation characteristic have ability to deal with nonlinear and non-Gaussian problems so it were widely used. There are various forms of density in the particle filter algorithm to make it valid when target occlusion occurred or recover tracking back from failure in track procedure but in order to capture the change of the state space it need a certain amount of particles to ensure samples is enough and this number will increase in accompany with dimension and increase exponentially this led to the increased amount of calculation is presented. In this paper particle filter algorithm and the Mean shift will be combined. Aiming at deficiencies of the classic mean shift Tracking algorithm easily trapped into local minima and Unable to get global optimal under the complex background. From these two perspectives that "adaptive multiple information fusion" and "with particle filter framework combining" we expand the classic Mean Shift tracking framework.Based on the previous perspective we proposed an improved Mean Shift infrared target tracking algorithm based on multiple information fusion. In the analysis of the infrared characteristics of target basis Algorithm firstly extracted target gray and edge character and Proposed to guide the above two characteristics by the moving of the target information thus we can get new sports guide grayscale characteristics and motion guide border feature. Then proposes a new adaptive fusion mechanism used these two new information adaptive to integrate into the Mean Shift tracking framework. Finally we designed a kind of automatic target model updating strategy to further improve tracking performance. Experimental results show that this algorithm can compensate shortcoming of the particle filter has too much computation and can effectively overcome the fault that mean shift is easy to fall into local extreme value instead of global maximum value.Last because of the gray and fusion target motion information this approach also inhibit interference from the background ultimately improve the stability and the real-time of the target track. 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).
	A UD factorization-based nonlinear adaptive set-membership filter for ellipsoidal estimation 期刊论文 OAI收割 International Journal of Robust and Nonlinear Control, 2008, 卷号: 18, 期号: 16, 页码: 1513-1531 作者: Zhou B(周波); Han JD(韩建达); Liu GJ(刘光军) 收藏 \| 浏览/下载：26/0 \| 提交时间：2012/05/29 set-membership filter UD factorization nonlinear state and parameter estimation adaptive filter parameter determination
	Study on integrated vehicle navigation system of "Beidou" double-star/DR (EI CONFERENCE) 会议论文 OAI收割 ICO20: Optical Devices and Instruments, August 21, 2005 - August 26, 2005, Changchun, China 作者: Liu J.; Liu J.; Liu J.; Liu H.; Liu H. 收藏 \| 浏览/下载：29/0 \| 提交时间：2013/03/25 Vehicle navigation is the corn element of Intelligent Transport System. The integrated system of "Beidou" Double-star/DR is studied in this paper according to the present state of vehicle navigation in our country. "Beidou" Double-star navigation position system is one regional satellite position system built up by our country which can provide rapidly not only highly precision position and brevity telegram service. However when the vehicles go around the tall buildings high mountain area wayside trees and in the tunnels all signal may not be received. If the satellite navigation position system is used only the precision will be reduced. Therefore this paper proposes a nonlinear self-adaptive Kalman filter model and its algorithm for a Double-star/DR integrated navigation system in land vehicles and verifies effectively the algorithm and scheme through the means of simulation. Next this paper introduces map match approach. The roads are segmented and character information is brought out. Then proper search rules and map match algorithm are adopted. According to the current vehicle position information that Double-Star/DR system provides the nearest road can be found in the map database. The vehicle position will be matched and displayed on the road. The result of the experiment shows that the Double-star/DR integrated algorithm and map match can improve reliability and the precision of vehicle navigation system efficiently.