Ridge Estimation-Based Vision and Laser Ranging Fusion Localization Method for UAVs
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arXiv
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866912773304221696 |
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| author | Huang, Huayu Chen, Chen Guan, Banglei Tan, Ze Shang, Yang Li, Zhang Yu, Qifeng |
| author_facet | Huang, Huayu Chen, Chen Guan, Banglei Tan, Ze Shang, Yang Li, Zhang Yu, Qifeng |
| contents | Tracking and measuring targets using a variety of sensors mounted on UAVs is an effective means to quickly and accurately locate the target. This paper proposes a fusion localization method based on ridge estimation, combining the advantages of rich scene information from sequential imagery with the high precision of laser ranging to enhance localization accuracy. Under limited conditions such as long distances, small intersection angles, and large inclination angles, the column vectors of the design matrix have serious multicollinearity when using the least squares estimation algorithm. The multicollinearity will lead to ill-conditioned problems, resulting in significant instability and low robustness. Ridge estimation is introduced to mitigate the serious multicollinearity under the condition of limited observation. Experimental results demonstrate that our method achieves higher localization accuracy compared to ground localization algorithms based on single information. Moreover, the introduction of ridge estimation effectively enhances the robustness, particularly under limited observation conditions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_16314 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Ridge Estimation-Based Vision and Laser Ranging Fusion Localization Method for UAVs Huang, Huayu Chen, Chen Guan, Banglei Tan, Ze Shang, Yang Li, Zhang Yu, Qifeng Computer Vision and Pattern Recognition Tracking and measuring targets using a variety of sensors mounted on UAVs is an effective means to quickly and accurately locate the target. This paper proposes a fusion localization method based on ridge estimation, combining the advantages of rich scene information from sequential imagery with the high precision of laser ranging to enhance localization accuracy. Under limited conditions such as long distances, small intersection angles, and large inclination angles, the column vectors of the design matrix have serious multicollinearity when using the least squares estimation algorithm. The multicollinearity will lead to ill-conditioned problems, resulting in significant instability and low robustness. Ridge estimation is introduced to mitigate the serious multicollinearity under the condition of limited observation. Experimental results demonstrate that our method achieves higher localization accuracy compared to ground localization algorithms based on single information. Moreover, the introduction of ridge estimation effectively enhances the robustness, particularly under limited observation conditions. |
| title | Ridge Estimation-Based Vision and Laser Ranging Fusion Localization Method for UAVs |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2512.16314 |