Research on Registration Methods for Coupled Errors in Maneuvering Platforms
The performance limitations of single-sensor systems in target tracking have led to the widespread adoption of multi-sensor fusion, which improves accuracy through information complementarity and redundancy. However, on mobile platforms, dynamic changes in sensor attitude and position introduce coup...
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MDPI AG
2025-06-01
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| Online Access: | https://www.mdpi.com/1099-4300/27/6/607 |
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| author | Qiang Li Ruidong Liu Yalei Liu Zhenzhong Wei |
| author_facet | Qiang Li Ruidong Liu Yalei Liu Zhenzhong Wei |
| author_sort | Qiang Li |
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| description | The performance limitations of single-sensor systems in target tracking have led to the widespread adoption of multi-sensor fusion, which improves accuracy through information complementarity and redundancy. However, on mobile platforms, dynamic changes in sensor attitude and position introduce coupled measurement and attitude errors, making accurate sensor registration particularly challenging. Most existing methods either treat these errors independently or rely on simplified assumptions, which limit their effectiveness in dynamic environments. To address this, we propose a novel joint error estimation and registration method based on a pseudo-Kalman filter (PKF). The PKF constructs pseudo-measurements by subtracting outputs from multiple sensors, projecting them into a bias space that is independent of the target’s state. A decoupling mechanism is introduced to distinguish between measurement and attitude error components, enabling accurate joint estimation in real time. In the shipborne environment, simulation experiments on pitch, yaw, and roll motions were conducted using two sensors. This method was compared with least squares (LS), maximum likelihood (ML), and the standard method based on PKF. The results show that the method based on PKF has a lower root mean square error (RMSE), a faster convergence speed, and better estimation accuracy and robustness. The proposed approach provides a practical and scalable solution for sensor registration in dynamic environments, particularly in maritime or aerial applications where coupled errors are prevalent. |
| format | Article |
| id | doaj-art-aafca521a12e40c48e491dd1d1f1077d |
| institution | Matheson Library |
| issn | 1099-4300 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj-art-aafca521a12e40c48e491dd1d1f1077d2025-06-25T13:48:37ZengMDPI AGEntropy1099-43002025-06-0127660710.3390/e27060607Research on Registration Methods for Coupled Errors in Maneuvering PlatformsQiang Li0Ruidong Liu1Yalei Liu2Zhenzhong Wei3School of Instrumentation and Optoelectronics Engineering, Beihang University, Beijing 100083, ChinaSchool of Artificial Intelligence, Henan University, Zhengzhou 450046, ChinaSchool of Artificial Intelligence, Henan University, Zhengzhou 450046, ChinaSchool of Instrumentation and Optoelectronics Engineering, Beihang University, Beijing 100083, ChinaThe performance limitations of single-sensor systems in target tracking have led to the widespread adoption of multi-sensor fusion, which improves accuracy through information complementarity and redundancy. However, on mobile platforms, dynamic changes in sensor attitude and position introduce coupled measurement and attitude errors, making accurate sensor registration particularly challenging. Most existing methods either treat these errors independently or rely on simplified assumptions, which limit their effectiveness in dynamic environments. To address this, we propose a novel joint error estimation and registration method based on a pseudo-Kalman filter (PKF). The PKF constructs pseudo-measurements by subtracting outputs from multiple sensors, projecting them into a bias space that is independent of the target’s state. A decoupling mechanism is introduced to distinguish between measurement and attitude error components, enabling accurate joint estimation in real time. In the shipborne environment, simulation experiments on pitch, yaw, and roll motions were conducted using two sensors. This method was compared with least squares (LS), maximum likelihood (ML), and the standard method based on PKF. The results show that the method based on PKF has a lower root mean square error (RMSE), a faster convergence speed, and better estimation accuracy and robustness. The proposed approach provides a practical and scalable solution for sensor registration in dynamic environments, particularly in maritime or aerial applications where coupled errors are prevalent.https://www.mdpi.com/1099-4300/27/6/607error calibrationmobile platform sensor registrationinformation entropycoupled error estimationmutual information couplingpseudo-Kalman filter (PKF) |
| spellingShingle | Qiang Li Ruidong Liu Yalei Liu Zhenzhong Wei Research on Registration Methods for Coupled Errors in Maneuvering Platforms Entropy error calibration mobile platform sensor registration information entropy coupled error estimation mutual information coupling pseudo-Kalman filter (PKF) |
| title | Research on Registration Methods for Coupled Errors in Maneuvering Platforms |
| title_full | Research on Registration Methods for Coupled Errors in Maneuvering Platforms |
| title_fullStr | Research on Registration Methods for Coupled Errors in Maneuvering Platforms |
| title_full_unstemmed | Research on Registration Methods for Coupled Errors in Maneuvering Platforms |
| title_short | Research on Registration Methods for Coupled Errors in Maneuvering Platforms |
| title_sort | research on registration methods for coupled errors in maneuvering platforms |
| topic | error calibration mobile platform sensor registration information entropy coupled error estimation mutual information coupling pseudo-Kalman filter (PKF) |
| url | https://www.mdpi.com/1099-4300/27/6/607 |
| work_keys_str_mv | AT qiangli researchonregistrationmethodsforcouplederrorsinmaneuveringplatforms AT ruidongliu researchonregistrationmethodsforcouplederrorsinmaneuveringplatforms AT yaleiliu researchonregistrationmethodsforcouplederrorsinmaneuveringplatforms AT zhenzhongwei researchonregistrationmethodsforcouplederrorsinmaneuveringplatforms |