Results 171 to 180 of about 8,181 (194)

Intelligent adaptive unscented particle filter with application in target tracking

Signal, Image and Video Processing, 2020
The particle filter (PF) perform the nonlinear estimation and have received much attention from many engineering fields over the past decade. However, the standard PF is inconsistent over time due to the loss of particle diversity caused mainly by the particle depletion in resampling step and incorrect a priori knowledge of process and measurement ...
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A comparison between Unscented Kalman Filtering and particle filtering for RSSI-based tracking

2010 7th Workshop on Positioning, Navigation and Communication, 2010
The task of tracking targets carrying active radio-frequency identification (RFID) tags based on the received signal strength indication (RSSI) values of tag transmissions is a classical Bayesian filtering problem. Since the problem is nonlinear, no closed-form solution is known and tractable approximations must be used. Unscented Kalman Filtering (UKF)
Kung-Chung Lee, Anand Oka, Emmanuel Pollakis, Lutz H.-J. Lampe   +3 more
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Unscented particle filter with estimation windows in submarine tracking

2010 8th World Congress on Intelligent Control and Automation, 2010
In order to estimate the state of uncertain models, a robust filter based on risk sensitive estimator is proposed, which could automatically change the state noise covariance according to the magnitude of the risk function. As a result, sample impoverishment could be mitigated. Another contribution of this paper is to take every sensor measurement into
null Shenmin Song, null Xiqing Wei, null Peng Li, null Baoqun Zhang   +3 more
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A new FastSLAM algorithm based on the unscented particle filter

2018 Chinese Control And Decision Conference (CCDC), 2018
With the development of the artificial intelligence technology, mobile robots have been widely applied to various fields, such as human-computer interaction and self-cruise. Simultaneous localization and mapping is a key to realize the intelligent navigation.
Jie Luo, Lei Sun, Yunhui Jia
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An improved unscented particle filter for visual hand tracking

2010 3rd International Congress on Image and Signal Processing, 2010
Hand tracking is an active research topic in Human Computer Interaction (HCI). In this paper, we present an improved Unscented Particle Filter (UPF) combined with the incremental Principle Component Analysis (IPCA) method for the visual hand tracking. The Singular Value Decomposition (SVD) approach is introduced to compute the sigma points and then to ...
Hanxuan Yang, Zhan Song, Runen Chen
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Iterated square root unscented Kalman particle filter

2010 IEEE Youth Conference on Information, Computing and Telecommunications, 2010
In order to improve tracking estimation accuracy of square-root unscented Kalman particle filter (SRUKFPF), a new particle filter algorithm of update SRUKF based on iterated measurements is proposed. The algorithm produces the important density function of particle filter using maximum posteriori estimate of iterated square-root unscented Kalman filter,
null Guohui Li, null Hong Yang
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Adaptive unscented particle filter based on predicted residual

2011 6th IEEE Joint International Information Technology and Artificial Intelligence Conference, 2011
In order overcome the particle degradation and non-adjusted online in the traditional particle filter algorithm, an adaptive un scented particle filter algorithm based on predicted residual is proposed. The algorithm adopts a new proposal distribution combing the unscented kalman filter with the adaptive factor.
Hua-jian Wang, Zhan-rong Jing
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A target estimation algorithm based on unscented particle filter

2017 2nd International Conference on Robotics and Automation Engineering (ICRAE), 2017
Aiming at the problem of target information acquisition in passive homing guidance, a target estimation algorithm is designed based on the unscented particle filter. Particle filtering is not constrained by Gaussian hypothesis and linearity, and the global optimal state estimation can be realized.
Humin Lei, Ningbo Li, Lei Shao, Jinchang Liu, Jie Li   +4 more
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Unscented Particle Filter Algorithm for Ballistic Target Tracking

Applied Mechanics and Materials, 2014
At present, the ballistic Target tracking has a higher demand in convergence rate and tracking precision of filter algorithm. In the paper, a filter algorithm was improved based on particle filter. The algorithm was carried out from the aspects such as particle degradation and particle diversity lack.
Yan Zhai, Xiao Bo Guo, Yong Gang Yan
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A One-Step Unscented Particle Filter for Nonlinear Dynamical Systems

2007
This paper proposes a one-step unscented particle filter for accurate nonlinear estimation. Its design involves the elaboration of a reliable one-step unscented filter that draws state samples deterministically for doing both the time and measurement updates, without linearization of the observation model. Empirical investigations show that the onestep
Nikolay Y. Nikolaev, Evgueni N. Smirnov
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