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Motion trajectory prediction based on a CNN-LSTM sequential model
2020
Science China Information Sciences
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First, a box plot is used to detect and eliminate abnormal values of vehicle trajectories, and valid trajectory data are obtained. ...
In this study, we propose a trajectory prediction method based on a sequential model, that fuses two neural networks of a convolutional neural network (CNN) and a long short-term memory network (LSTM). ...
the standard based on the actual data drawing. ...
doi:10.1007/s11432-019-2761-y
fatcat:nq363xd4sjgtfc2jfci52z6sma
Kernel Entropy Based Extended Kalman Filter for GPS Navigation Processing
2021
Computers Materials & Continua
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The GPS navigation algorithm based on kernel entropy related principles, including the MEE criterion and the MCC will be performed, which is utilized not only for the time-varying adaptation but the outlier ...
errors or outliers of the GPS. ...
The gradient based methods are simple and widely used. However, they depend on a free parameter step-size and usually converge to an optimal solution slowly. ...
doi:10.32604/cmc.2021.016894
fatcat:lkvlw2osc5horknujf6gh3dz54
An Outlier Robust Finite Impulse Response Filter with Maximum Correntropy
2021
IEEE Access
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To improve the filtering performance degradation caused by improper kernel size, an adaptive kernel size algorithm is further proposed, which adjusts the bandwidth within a specific range adaptively and ...
An illustrative example based on moving target tracking is presented to evaluate the performance of the proposed filter, and simulation results confirmed that the MCFIR filter obtained superior immunity ...
Therefore, an adaptive filter with variable kernel size in [23] , and MCKF with adaptive kernel size in [24] were proposed to solve the problem. ...
doi:10.1109/access.2021.3053212
fatcat:s46ttxqd4jhsxkf4aewl5agl74
Uncertainty Quantification for PTV/LPT data and Adaptive Track Filtering
2021
14th International Symposium on Particle Image Velocimetry
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Based on these uncertainties, an adaptive filtering approach is introduced, which eliminates the user's choice of the filter kernel length and which automatically determines its optimal value. ...
The most recent research focused mainly on algorithmic advancements in order to increase the obtainable data density and on its application to new flow cases. ...
Based on these uncertainties, an adaptive filtering approach is introduced, which eliminates the user's choice of the filter kernel length and which automatically determines its optimal value. 2 Uncertainty ...
doi:10.18409/ispiv.v1i1.125
fatcat:cs5wfcluc5bd5nkbjipiguxhc4
A New Robust Adaptive Filter Aided by Machine Learning Method for SINS/DVL Integrated Navigation System
2022
Sensors
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Therefore, this paper proposes a new adaptive filter based on support vector regression. ...
Instead, outliers are eliminated from the perspective of external sensors, which effectively improves the robustness of the filter. ...
[33] proposes a robust Kalman filter (ODKF) with outlier detection, which utilizes a binary indicator variable to mark outliers and eliminate them. Ref. ...
doi:10.3390/s22103792
pmid:35632201
pmcid:PMC9144316
fatcat:ckuvr6l6cjgild77buqvm5cyo4
Support Vector Regression Based on Grid-Search Method for Short-Term Wind Power Forecasting
2014
Journal of Applied Mathematics
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by multiscale support vector regression (SVR) technique, and the parameters associated with SVR are optimized based on Grid-search method. ...
The two main contributions of this paper are as follows. (1) In data preprocessing, each encountered problem of employed real data such as irrelevant, outliers, missing value, and noisy data has been taken ...
Acknowledgments The authors would like to thank the Professor Hongjie Jia and editor Dean who gave valuable comments by means of considerable suggestion and comments which improved highly the quality of ...
doi:10.1155/2014/835791
fatcat:vxsqyudpnvhh7l5x2mq54aecoe
Outlier Detection of Crowdsourcing Trajectory Data Based on Spatial and Temporal Characterization
2023
Mathematics
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As an emerging type of spatio-temporal big data based on positioning technology and navigation devices, vehicle-based crowdsourcing data has become a valuable trajectory data resource. ...
Specifically, we first use the adaptive spatial clustering algorithm based on the Delaunay triangulation (ASCDT) algorithm to remove the location offset points in the trajectory sequence. ...
Acknowledgments: The authors also thank the associate editor and the reviewers for their useful feedback that improved this paper.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/math11030620
fatcat:cd4cbmzhrff37n3bkztecb5dey
Underwater Vehicle Positioning by Correntropy-Based Fuzzy Multi-Sensor Fusion
2021
Sensors
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Multi-sensor fusion methods for underwater vehicle positioning are commonly based on Kalman filtering, which requires the knowledge of process and measurement noise covariance. ...
the presence of outliers. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/s21186165
pmid:34577372
pmcid:PMC8470692
fatcat:uetg2ibv3raibot5mrja7r45la
A Multiple-Step, Randomly Delayed, Robust Cubature Kalman Filter for Spacecraft-Relative Navigation
2023
Aerospace (Basel)
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Then, the MRD-DCSCKF uses the framework of the multiple-step randomly delayed filter, based on a state-augmentation approach, to address the problem of delayed measurements. ...
Meanwhile, it depends on a dynamic-covariance-scaling (DCS) robust kernel to reject the outliers in the measurements. ...
The proposed filter adopts a multiple-step, randomly delayed filtering framework to weaken the impact of delayed measurements on the estimation accuracy of the filter, and it suppresses outliers with a ...
doi:10.3390/aerospace10030289
fatcat:lrrfxogrtbhz5dl5zlusyaajdy
Research on Trajectory Recognition and Control Technology of Real-Time Tracking Welding
2022
Sensors
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Additionally, the embedded Pauta criterion was used to segmentally process the center point data stream and to cyclically eliminate outliers and further ensure the accuracy of the welding reference point ...
Real-time tracking welding with the assistance of structured light vision enhances the intelligence of robotic welding, which significantly shortens teaching time and guarantees accuracy for user-customized ...
Multiple convolutions based on the kernel of size 3 × 3, after that, the output of the picture was changed to a one-dimensional vector; 3. ...
doi:10.3390/s22218546
pmid:36366244
pmcid:PMC9657757
fatcat:sahktgmpfrhxrlsdzugyw5yeba
The Millimeter-Wave Radar SLAM Assisted by the RCS Feature of the Target and IMU
2020
Sensors
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The Density-based Spatial Clustering of Applications with Noise (DBSCAN) clustering algorithm is used to filter outliers from radar data. ...
Based on the comparison of the experimental results, it is proved that the proposed millimeter-wave radar SLAM assisted by the RCS feature of the target and IMU has better accuracy and robustness in the ...
We also thank Yelin Qiu and Baixiang Qiang for providing data for this research.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/s20185421
pmid:32971798
pmcid:PMC7570575
fatcat:xrie5cb3bjdsxoxqw33iqvwlje
Improved Vessel Trajectory Prediction Model Based on Stacked-BiGRUs
2022
Security and Communication Networks
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In this study, we propose a novel vessel trajectory prediction model for accurate prediction with the following characteristics: (1) an anchor trajectory elimination algorithm to eliminate anchor trajectories ...
However, certain characteristics in the AIS data, such as the large number of anchored trajectories in the area, anomalous sharp turns of some trajectories, and the behavioral differences of vessels in ...
Trajectory Prediction Based on Dynamic Model Analysis. e Kalman filter is a classic method in the field of linear system analysis. ...
doi:10.1155/2022/8696558
doaj:eacb1880366e49689c8cc090d676a291
fatcat:fiv4epmadvdrfclnqplt3ziy5a
Mining Streaming and Temporal Data: from Representation to Knowledge
2018
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence
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Knowledge discovery based on the new representations will then be computationally efficient, and to certain extent be more effective due to the removal of noise and irrelevant information in the step of ...
Representation learning facilitates the data operation by providing a condensed description of patterns underlying the data. ...
kernels of user representations modeled by Kalman filter. ...
doi:10.24963/ijcai.2018/821
dblp:conf/ijcai/Zhang18
fatcat:nygi5fmzm5gnbe6o7sovz3e6nm
Mean shift: a robust approach toward feature space analysis
2002
IEEE Transactions on Pattern Analysis and Machine Intelligence
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The equivalence of the mean shift procedure to the Nadaraya-Watson estimator from kernel regression and the robust M-estimators of location is also established. ...
We prove for discrete data the convergence of a recursive mean shift procedure to the nearest stationary point of the underlying density function and thus its utility in detecting the modes of the density ...
Acknowledgment The support of the National Science Foundation under the grants IRI 95-30546 and IRI 99-87695 is gratefully acknowledged. ...
doi:10.1109/34.1000236
fatcat:udopohklrjdutncnwhb3vvmetm
Structured Kernel Subspace Learning for Autonomous Robot Navigation
2018
Sensors
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basis, which eliminates the effects of erroneous and inconsistent data. ...
challenges, such as the varying quality and complexity of training data with unwanted noises. ...
FactGP M and PITC use kernel matrices whose ranks are either 20% or 40% of the size of the original kernel matrix: (a) No outliers with 20% low-rank; (b) no outliers with 40% low-rank; (c) 20% outliers ...
doi:10.3390/s18020582
pmid:29443897
pmcid:PMC5856188
fatcat:gxkwy433hjhhrdrzxriwpfoxue
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