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A New Adaptive Robust Unscented Kalman Filter for Improving the Accuracy of Target Tracking

Weidong Zhou, Jiaxin Hou
<span title="">2019</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q7qi7j4ckfac7ehf3mjbso4hne" style="color: black;">IEEE Access</a> </i> &nbsp;
INDEX TERMS Nonlinear system, unscented Kalman filter (UKF), nonlinear filtering, adaptive robust Kalman filter. 77476 2169-3536  ...  of outliers, non-Gaussian noise as well as a model error to achieve high accuracy state estimation.  ...  Gaussian-Hermite filter (GHF), cubature Kalman filter (CKF), unscented Kalman filter (UKF) and particle filter (PF).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2019.2921794">doi:10.1109/access.2019.2921794</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/vdrxqbn7hrf3njlcuiqpjnq33q">fatcat:vdrxqbn7hrf3njlcuiqpjnq33q</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210428192152/https://ieeexplore.ieee.org/ielx7/6287639/8600701/08733790.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/38/ca/38cacbb2345cde2d10507ac0912fa4c124bb0810.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2019.2921794"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> ieee.com </button> </a>

Adaptive Robust Unscented Kalman Filter via Fading Factor and Maximum Correntropy Criterion

Zhihong Deng, Lijian Yin, Baoyu Huo, Yuanqing Xia
<span title="2018-07-24">2018</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/taedaf6aozg7vitz5dpgkojane" style="color: black;">Sensors</a> </i> &nbsp;
In order to suppress the impact of observation outliers in the process of target tracking, a novel filtering algorithm, namely a robust adaptive unscented Kalman filter, is proposed.  ...  Finally, the simulation results show that the presented algorithm has good performance, and it improves the robustness of a general unscented Kalman filter and solves the problem of outliers in system.  ...  In our research, tracking a moving target by a sensor has been carried out to compare with UKF and an adaptive Huber unscented Kalman filter [24] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s18082406">doi:10.3390/s18082406</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/30042346">pmid:30042346</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/o3ue6xigizdpva7iazv26qct7i">fatcat:o3ue6xigizdpva7iazv26qct7i</a> </span>
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Maximum Correntropy Criterion Kalman Filter for α-Jerk Tracking Model with Non-Gaussian Noise

Bowen Hou, Zhangming He, Xuanying Zhou, Haiyin Zhou, Dong Li, Jiongqi Wang
<span title="2017-11-29">2017</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/4d3elkqvznfzho6ki7a35bt47u" style="color: black;">Entropy</a> </i> &nbsp;
Huber-based robust filter is a classical method to handle the non-Gaussian noises and outliers [26] .  ...  The first approach is to develop filters for the systems with non-Gaussian noises directly.  ...  The α-Jerk model results obtained by the Huber-based filter (HF), ensemble Kalman filter (EnKF), unscented Kalman filter (UKF), Gaussian sum filter (GSF) and maximum correntropy criterion Kalman filter  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/e19120648">doi:10.3390/e19120648</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/avzwdumrp5enrcogulznn2r6b4">fatcat:avzwdumrp5enrcogulznn2r6b4</a> </span>
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Robust Huber-Based Cubature Kalman Filter for GPS Navigation Processing

Chien-Hao Tseng, Sheng-Fuu Lin, Dah-Jing Jwo
<span title="2016-10-19">2016</span> <i title="Cambridge University Press (CUP)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/wdjwdlvocrhrdgu4pc2j4hkmni" style="color: black;">Journal of navigation</a> </i> &nbsp;
For the signals contaminated with non-Gaussian noise or outliers, a robust scheme combining the Huber M-estimation methodology and the CKF framework is beneficial where the Huber M-estimation methodology  ...  A robust state estimation technique based on the Huber-based Cubature Kalman Filter (HCKF) is proposed for Global Positioning System (GPS) navigation processing.  ...  This paper has presented a Huber-based Cubature Kalman Filter (HCKF) for GPS navigation processing. The measurements are GPS pseudorange observables contaminated with non-Gaussian errors.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1017/s0373463316000692">doi:10.1017/s0373463316000692</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/j2om63vxq5gdpnplyaaq5bkbui">fatcat:j2om63vxq5gdpnplyaaq5bkbui</a> </span>
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Maximum correntropy unscented filter

Xi Liu, Badong Chen, Bin Xu, Zongze Wu, Paul Honeine
<span title="2017-01-11">2017</span> <i title="Informa UK Limited"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/lbkovrgvnbhrdnfuwbzssw2vsq" style="color: black;">International Journal of Systems Science</a> </i> &nbsp;
Applying the UT to a Kalman filter type estimator leads to the well-known unscented Kalman filter (UKF).  ...  Although the UKF works very well in Gaussian noises, its performance may deteriorate significantly when the noises are non-Gaussian, especially when the system is disturbed by some heavy-tailed impulsive  ...  The goal of this paper is to develop an unscented non-linear Kalman type filter based on the MCC, called the maximum correntropy unscented filter (MCUF).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1080/00207721.2016.1277407">doi:10.1080/00207721.2016.1277407</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/4j2t543cxneotjl7mpp6fukkim">fatcat:4j2t543cxneotjl7mpp6fukkim</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190308151050/http://pdfs.semanticscholar.org/f518/dc46d5993a66778d4bdf151f5fe592926dda.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/f5/18/f518dc46d5993a66778d4bdf151f5fe592926dda.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1080/00207721.2016.1277407"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> tandfonline.com </button> </a>

Maximum Correntropy Based Unscented Particle Filter for Cooperative Navigation with Heavy-Tailed Measurement Noises

Ying Fan, Yonggang Zhang, Guoqing Wang, Xiaoyu Wang, Ning Li
<span title="2018-09-20">2018</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/taedaf6aozg7vitz5dpgkojane" style="color: black;">Sensors</a> </i> &nbsp;
As compared with the classic unscented particle filter (UPF) based on Gaussian assumption of measurement noise, the proposed robust particle filter based on the maximum correntropy criterion (MCC) exhibits  ...  for CN systems with heavy-tailed measurement noises, and the proposed MCUPF has lower computational complexity than existing robust particle filters.  ...  The PDF of Gaussian noise v 1 ( v 1 ∼ N(0, R), R = 10), heavy-tailed non-Gaussian noises v 2 (generated based on Equation (1) with ε = 0.1) and heavy-tailed non-Gaussian noises v 3 (generated based on  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s18103183">doi:10.3390/s18103183</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/30241388">pmid:30241388</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC6209909/">pmcid:PMC6209909</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/t4v3xoyzcbaqzn36y645j6gj3e">fatcat:t4v3xoyzcbaqzn36y645j6gj3e</a> </span>
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Maximum Correntropy Unscented Kalman Filter for Spacecraft Relative State Estimation

Xi Liu, Hua Qu, Jihong Zhao, Pengcheng Yue, Meng Wang
<span title="2016-09-20">2016</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/taedaf6aozg7vitz5dpgkojane" style="color: black;">Sensors</a> </i> &nbsp;
In this paper, a non-linear Kalman type filter based on MCC has been derived, namely the maximum correntropy unscented Kalman filter (MCUKF).  ...  As is well known, the unscented Kalman filter (UKF) provides an efficient tool to solve the non-linear state estimate problem. However, the UKF usually plays well in Gaussian noises.  ...  Figure 7 . 7 MSD v with different filters in non-Gaussian noises.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s16091530">doi:10.3390/s16091530</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/27657069">pmid:27657069</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC5038803/">pmcid:PMC5038803</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/xq4wkpjlwzc6xc6gna2eokztiq">fatcat:xq4wkpjlwzc6xc6gna2eokztiq</a> </span>
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Maximum Correntropy Unscented Filter [article]

Xi Liu, Badong Chen, Bin Xu, Zongze Wu, Paul Honeine
<span title="2016-08-26">2016</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Applying the UT to a Kalman filter type estimator leads to the well-known unscented Kalman filter (UKF).  ...  Although the UKF works very well in Gaussian noises, its performance may deteriorate significantly when the noises are non-Gaussian, especially when the system is disturbed by some heavy-tailed impulsive  ...  The goal of this paper is to develop an unscented nonlinear Kalman type filter based on the MCC, called the maximum correntropy unscented filter (MCUF).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1608.07526v1">arXiv:1608.07526v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ag7ulvit6rfu7a6ok6nlewpkxq">fatcat:ag7ulvit6rfu7a6ok6nlewpkxq</a> </span>
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Gaussian Filter based on Deterministic Sampling for High Quality Nonlinear Estimation

Marco F. Huber, Uwe D. Hanebeck
<span title="">2008</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/p3wtlm3j2fedxitkuu4bs3scau" style="color: black;">IFAC Proceedings Volumes</a> </i> &nbsp;
The improved performance of the proposed Gaussian filter compared to the well-known unscented Kalman filter is demonstrated by means of two examples.  ...  In this paper, a Gaussian filter for nonlinear Bayesian estimation is introduced that is based on a deterministic sample selection scheme.  ...  ., non-equal weighting coefficients and non-Gaussian densities can be considered.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3182/20080706-5-kr-1001.02291">doi:10.3182/20080706-5-kr-1001.02291</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/a6y2f53ykrbtflovmyz7g4x3aq">fatcat:a6y2f53ykrbtflovmyz7g4x3aq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20151224023344/http://isas.uka.de/Publikationen/IFAC08_Huber.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/b0/f8/b0f8c64e809392d04ec639f56450f55ddfce0fa1.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3182/20080706-5-kr-1001.02291"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Huber-Based Divided Difference Filtering

Christopher D. Karlgaard, Hanspeter Schaub
<span title="">2007</span> <i title="American Institute of Aeronautics and Astronautics (AIAA)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/yekwqy6srncl5bew6tynp7vjsq" style="color: black;">Journal of Guidance Control and Dynamics</a> </i> &nbsp;
However, for non-Gaussian error distributions, the modified filters with the Huber update outperformed the standard filters.  ...  It is important to note that the SPKFs use a minimum /,-norm measurement update and are therefore subject to the same sensitivity to non-Gaussian measurement errors as the Kalman filter.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.2514/1.27968">doi:10.2514/1.27968</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/p56yl3trmvefhisfecnosyjrdq">fatcat:p56yl3trmvefhisfecnosyjrdq</a> </span>
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RCKF Cooperative Navigation Algorithm for Tightly Coupled Vehicle Ad Hoc Networks Based on Huber M Estimation

Wei Sun, Jingzhou Liu
<span title="">2021</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q7qi7j4ckfac7ehf3mjbso4hne" style="color: black;">IEEE Access</a> </i> &nbsp;
ROBUST CUBATURE KALMAN FILTER CKF is based on the L2 norm estimation of the Gaussian noise distribution. The L2 norm estimation squares the error and amplifies the outliers.  ...  In 1997, Juliter proposed the unscented Kalman filter (UKF), which is based on the view that "it is much easier to approximate the probability distribution of a nonlinear function than a nonlinear function  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2021.3118778">doi:10.1109/access.2021.3118778</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/zps2fggarzajvhlr3xtzavvrqq">fatcat:zps2fggarzajvhlr3xtzavvrqq</a> </span>
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Adaptive Gaussian Mixture Filter Based on Statistical Linearization [article]

Marco F. Huber
<span title="2012-03-30">2012</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
In this paper, an adaptive Gaussian mixture filter based on statistical linearization is proposed.  ...  Gaussian mixtures are a common density representation in nonlinear, non-Gaussian Bayesian state estimation.  ...  In this paper, an adaptive Gaussian mixture filter based on statistical linearization is proposed.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1203.6750v1">arXiv:1203.6750v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/zfyv3cdknbhy5ekwbbbyxxtvg4">fatcat:zfyv3cdknbhy5ekwbbbyxxtvg4</a> </span>
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Correntropy Based Divided Difference Filtering for the Positioning of Ships

Xi Liu, Badong Chen, Shiyuan Wang, Shaoyi Du
<span title="2018-11-21">2018</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/taedaf6aozg7vitz5dpgkojane" style="color: black;">Sensors</a> </i> &nbsp;
robustness in the presence of non-Gaussian noises, especially when the measurements are contaminated by heavy-tailed noises.  ...  In this paper, robust first and second-order divided difference filtering algorithms based on correntropy are proposed, which not only retain the advantages of divided difference filters, but also exhibit  ...  Figure 3 . 3 MSEs of λ with first-order approximate filters in non-Gaussian noises. Figure 4 . 4 MSEs of ϕ with second-order approximate filters in non-Gaussian noises.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s18114080">doi:10.3390/s18114080</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/30469453">pmid:30469453</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/b2mw46bzyfdy5czahdj3gbneoe">fatcat:b2mw46bzyfdy5czahdj3gbneoe</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190302025047/http://pdfs.semanticscholar.org/ae55/948bf34c64de78fa993b2c28948656c9bc31.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/ae/55/ae55948bf34c64de78fa993b2c28948656c9bc31.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s18114080"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

Robust Student's t based Stochastic Cubature Filter for Nonlinear Systems with Heavy-tailed Process and Measurement Noises [article]

Yulong Huang, Yonggang Zhang
<span title="2017-03-31">2017</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
In this paper, a new robust Student's t based stochastic cubature filter (RSTSCF) is proposed for nonlinear state-space model with heavy-tailed process and measurement noises.  ...  Simulation results show that the proposed RSTSCF can achieve higher estimation accuracy than the existing Gaussian approximate filter, Gaussian sum filter, Huber-based nonlinear Kalman filter, maximum  ...  filter [22] , the Huber-based unscented Kalman filter [23] , the nonlinear regression Huber Kalman filter [24] and the adaptively robust unscented Kalman filter (ARUKF) [25] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1704.00040v1">arXiv:1704.00040v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/xexfr4hqabdkfmpvltbaof44qi">fatcat:xexfr4hqabdkfmpvltbaof44qi</a> </span>
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An Outlier Robust Finite Impulse Response Filter with Maximum Correntropy

Yanda Guo, Xuyou Li, Qingwen Meng
<span title="">2021</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q7qi7j4ckfac7ehf3mjbso4hne" style="color: black;">IEEE Access</a> </i> &nbsp;
Non-Gaussian noise is common in industrial applications, and it is a severe challenge to existing state estimators.  ...  The filter operates as a finite memory form, and thus it obtains superior immunity to noise statistics and process uncertainties than existing Kalman-like robust filters.  ...  Recently, correntropy based filters have introduced the concept of information entropy as a local similarity measure, which is robust to non-Gaussian noise.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2021.3053212">doi:10.1109/access.2021.3053212</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/s46ttxqd4jhsxkf4aewl5agl74">fatcat:s46ttxqd4jhsxkf4aewl5agl74</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210716181835/https://ieeexplore.ieee.org/ielx7/6287639/9312710/09330603.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/b9/d8/b9d8d8eb47542a95628f6973241cd7188d4fb8f4.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2021.3053212"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> ieee.com </button> </a>
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