Event-Driven Maximum Correntropy Filter Based on Cauchy Kernel for Spatial Orientation Using Gyros/Star Sensor Integration
Gyros/star sensor integration provides a potential method to obtain high-accuracy spatial orientation for turntable structures. However, it is subjected to the problem of accuracy loss when the measurement noises become non-Gaussian due to the complex spatial environment. This paper presents an even...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-11-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/24/22/7164 |
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| author | Kai Cui Zhaohui Liu Junfeng Han Yuke Ma Peng Liu Bingbing Gao |
| author_facet | Kai Cui Zhaohui Liu Junfeng Han Yuke Ma Peng Liu Bingbing Gao |
| author_sort | Kai Cui |
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| description | Gyros/star sensor integration provides a potential method to obtain high-accuracy spatial orientation for turntable structures. However, it is subjected to the problem of accuracy loss when the measurement noises become non-Gaussian due to the complex spatial environment. This paper presents an event-driven maximum correntropy filter based on Cauchy kernel to handle the above problem. In this method, a direct installation mode of gyros/star sensor integration is established and the associated mathematical model is derived to improve the turntable’s control stability. Based on this, a Cauchy kernel-based maximum correntropy filter is developed to curb the influence of non-Gaussian measurement noise for enhancing the gyros/star sensor integration’s robustness. Subsequently, an event-driven mechanism is constructed based on the filter’s innovation information for further reducing the unnecessary computational cost to optimize the real-time performance. The effectiveness of the proposed method has been validated by simulations of the gyros/star sensor integration for spatial orientation. This shows that the proposed filtering methodology not only has strong robustness to deal with the influence of non-Gaussian measurement noise but can also achieve superior real-time spatial applications with a small computational cost, leading to enhanced performance for the turntable’s spatial orientation using gyros/star sensor integration. |
| format | Article |
| id | doaj-art-e24aefdae37148c48ae1c276cb546d73 |
| institution | OA Journals |
| issn | 1424-8220 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
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| series | Sensors |
| spelling | doaj-art-e24aefdae37148c48ae1c276cb546d732025-08-20T02:04:40ZengMDPI AGSensors1424-82202024-11-012422716410.3390/s24227164Event-Driven Maximum Correntropy Filter Based on Cauchy Kernel for Spatial Orientation Using Gyros/Star Sensor IntegrationKai Cui0Zhaohui Liu1Junfeng Han2Yuke Ma3Peng Liu4Bingbing Gao5University of Chinese Academy of Sciences, Beijing 100049, ChinaUniversity of Chinese Academy of Sciences, Beijing 100049, ChinaUniversity of Chinese Academy of Sciences, Beijing 100049, ChinaSchool of Automation, Northwestern Polytechnical University, Xi’an 710072, ChinaUniversity of Chinese Academy of Sciences, Beijing 100049, ChinaSchool of Automation, Northwestern Polytechnical University, Xi’an 710072, ChinaGyros/star sensor integration provides a potential method to obtain high-accuracy spatial orientation for turntable structures. However, it is subjected to the problem of accuracy loss when the measurement noises become non-Gaussian due to the complex spatial environment. This paper presents an event-driven maximum correntropy filter based on Cauchy kernel to handle the above problem. In this method, a direct installation mode of gyros/star sensor integration is established and the associated mathematical model is derived to improve the turntable’s control stability. Based on this, a Cauchy kernel-based maximum correntropy filter is developed to curb the influence of non-Gaussian measurement noise for enhancing the gyros/star sensor integration’s robustness. Subsequently, an event-driven mechanism is constructed based on the filter’s innovation information for further reducing the unnecessary computational cost to optimize the real-time performance. The effectiveness of the proposed method has been validated by simulations of the gyros/star sensor integration for spatial orientation. This shows that the proposed filtering methodology not only has strong robustness to deal with the influence of non-Gaussian measurement noise but can also achieve superior real-time spatial applications with a small computational cost, leading to enhanced performance for the turntable’s spatial orientation using gyros/star sensor integration.https://www.mdpi.com/1424-8220/24/22/7164maximum correntropy filterspatial orientationgyros/star sensor integrationnon-Gaussian noiseCauchy kernel |
| spellingShingle | Kai Cui Zhaohui Liu Junfeng Han Yuke Ma Peng Liu Bingbing Gao Event-Driven Maximum Correntropy Filter Based on Cauchy Kernel for Spatial Orientation Using Gyros/Star Sensor Integration Sensors maximum correntropy filter spatial orientation gyros/star sensor integration non-Gaussian noise Cauchy kernel |
| title | Event-Driven Maximum Correntropy Filter Based on Cauchy Kernel for Spatial Orientation Using Gyros/Star Sensor Integration |
| title_full | Event-Driven Maximum Correntropy Filter Based on Cauchy Kernel for Spatial Orientation Using Gyros/Star Sensor Integration |
| title_fullStr | Event-Driven Maximum Correntropy Filter Based on Cauchy Kernel for Spatial Orientation Using Gyros/Star Sensor Integration |
| title_full_unstemmed | Event-Driven Maximum Correntropy Filter Based on Cauchy Kernel for Spatial Orientation Using Gyros/Star Sensor Integration |
| title_short | Event-Driven Maximum Correntropy Filter Based on Cauchy Kernel for Spatial Orientation Using Gyros/Star Sensor Integration |
| title_sort | event driven maximum correntropy filter based on cauchy kernel for spatial orientation using gyros star sensor integration |
| topic | maximum correntropy filter spatial orientation gyros/star sensor integration non-Gaussian noise Cauchy kernel |
| url | https://www.mdpi.com/1424-8220/24/22/7164 |
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