Event-Driven Maximum Correntropy Filter Based on Cauchy Kernel for Spatial Orientation Using Gyros/Star Sensor Integration
Year: 2024
Type: article
Abstract: 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.
Source: Sensors
DOI: 10.3390/s24227164
Authors: Kai Cui, Zhaohui Liu, Junfeng Han, Yuke Ma, Peng Liu, Bingbing Gao
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,955
Funders: Chinese Academy of Sciences, Youth Innovation Promotion Association of the Chinese Academy of Sciences, Chinese Aeronautical Establishment, Youth Innovation Promotion Association, Key Research and Development Projects of Shaanxi Province, Basic and Applied Basic Research Foundation of Guangdong Province
OpenAlex ID: W4404136500
