Terrain-Aided Navigation Using a Point Cloud Measurement Sensor
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866914080260882432 |
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| author | Şanlan, Abdülbaki Erol, Fatih Abu-Khalaf, Murad Koyuncu, Emre |
| author_facet | Şanlan, Abdülbaki Erol, Fatih Abu-Khalaf, Murad Koyuncu, Emre |
| contents | We investigate the use of a point cloud measurement in terrain-aided navigation. Our goal is to aid an inertial navigation system, by exploring ways to generate a useful measurement innovation error for effective nonlinear state estimation. We compare two such measurement models that involve the scanning of a digital terrain elevation model: a) one that is based on typical ray-casting from a given pose, that returns the predicted point cloud measurement from that pose, and b) another computationally less intensive one that does not require raycasting and we refer to herein as a sliding grid. Besides requiring a pose, it requires the pattern of the point cloud measurement itself and returns a predicted point cloud measurement. We further investigate the observability properties of the altitude for both measurement models. As a baseline, we compare the use of a point cloud measurement performance to the use of a radar altimeter and show the gains in accuracy. We conclude by showing that a point cloud measurement outperforms the use of a radar altimeter, and the point cloud measurement model to use depends on the computational resources |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_06470 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Terrain-Aided Navigation Using a Point Cloud Measurement Sensor Şanlan, Abdülbaki Erol, Fatih Abu-Khalaf, Murad Koyuncu, Emre Systems and Control Robotics We investigate the use of a point cloud measurement in terrain-aided navigation. Our goal is to aid an inertial navigation system, by exploring ways to generate a useful measurement innovation error for effective nonlinear state estimation. We compare two such measurement models that involve the scanning of a digital terrain elevation model: a) one that is based on typical ray-casting from a given pose, that returns the predicted point cloud measurement from that pose, and b) another computationally less intensive one that does not require raycasting and we refer to herein as a sliding grid. Besides requiring a pose, it requires the pattern of the point cloud measurement itself and returns a predicted point cloud measurement. We further investigate the observability properties of the altitude for both measurement models. As a baseline, we compare the use of a point cloud measurement performance to the use of a radar altimeter and show the gains in accuracy. We conclude by showing that a point cloud measurement outperforms the use of a radar altimeter, and the point cloud measurement model to use depends on the computational resources |
| title | Terrain-Aided Navigation Using a Point Cloud Measurement Sensor |
| topic | Systems and Control Robotics |
| url | https://arxiv.org/abs/2510.06470 |