A Recursive Total Least Squares Solution for Bearing-Only Target Motion Analysis and Circumnavigation
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arXiv
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| Autori principali: | , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866908490916691968 |
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| author | Li, Lin Liu, Xueming Qiu, Zhoujingzi Hu, Tianjiang Zhang, Qingrui |
| author_facet | Li, Lin Liu, Xueming Qiu, Zhoujingzi Hu, Tianjiang Zhang, Qingrui |
| contents | Bearing-only Target Motion Analysis (TMA) is a promising technique for passive tracking in various applications as a bearing angle is easy to measure. Despite its advantages, bearing-only TMA is challenging due to the nonlinearity of the bearing measurement model and the lack of range information, which impairs observability and estimator convergence. This paper addresses these issues by proposing a Recursive Total Least Squares (RTLS) method for online target localization and tracking using mobile observers. The RTLS approach, inspired by previous results on Total Least Squares (TLS), mitigates biases in position estimation and improves computational efficiency compared to pseudo-linear Kalman filter (PLKF) methods. Additionally, we propose a circumnavigation controller to enhance system observability and estimator convergence by guiding the mobile observer in orbit around the target. Extensive simulations and experiments are performed to demonstrate the effectiveness and robustness of the proposed method. The proposed algorithm is also compared with the state-of-the-art approaches, which confirms its superior performance in terms of both accuracy and stability. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_11289 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Recursive Total Least Squares Solution for Bearing-Only Target Motion Analysis and Circumnavigation Li, Lin Liu, Xueming Qiu, Zhoujingzi Hu, Tianjiang Zhang, Qingrui Robotics Bearing-only Target Motion Analysis (TMA) is a promising technique for passive tracking in various applications as a bearing angle is easy to measure. Despite its advantages, bearing-only TMA is challenging due to the nonlinearity of the bearing measurement model and the lack of range information, which impairs observability and estimator convergence. This paper addresses these issues by proposing a Recursive Total Least Squares (RTLS) method for online target localization and tracking using mobile observers. The RTLS approach, inspired by previous results on Total Least Squares (TLS), mitigates biases in position estimation and improves computational efficiency compared to pseudo-linear Kalman filter (PLKF) methods. Additionally, we propose a circumnavigation controller to enhance system observability and estimator convergence by guiding the mobile observer in orbit around the target. Extensive simulations and experiments are performed to demonstrate the effectiveness and robustness of the proposed method. The proposed algorithm is also compared with the state-of-the-art approaches, which confirms its superior performance in terms of both accuracy and stability. |
| title | A Recursive Total Least Squares Solution for Bearing-Only Target Motion Analysis and Circumnavigation |
| topic | Robotics |
| url | https://arxiv.org/abs/2508.11289 |