This paper designs and implements a single-camera 360°panoramic imaging system based on motor-driven fisheye rotation.The system utilizes a stepper motor for precise angular control,enabling the camera to rotate ...This paper designs and implements a single-camera 360°panoramic imaging system based on motor-driven fisheye rotation.The system utilizes a stepper motor for precise angular control,enabling the camera to rotate around its optical center to capture multi-view images,thereby avoiding the parallax and geometric mismatch problems inherent in traditional multi-camera configurations.To address the strong distortion characteristics of fisheye images,an equidistant projection model is adopted for distortion correction.On this basis,a brightness normalization method combining global linear brightness correction and local illumination compensation is proposed to enhance stitching consistency.By establishing a geometry model constrained by camera rotation and integrating cylindrical projection with cosine-weighted blending,the system achieves high-precision panoramic stitching and seamless visual transitions.展开更多
In complicated urban environments,Global Navigation Satellite System(GNSS)signals are frequently affected by building reflection or refraction,resulting in Non-Line-of-Sight(NLOS)errors.In severe cases,NLOS errors can...In complicated urban environments,Global Navigation Satellite System(GNSS)signals are frequently affected by building reflection or refraction,resulting in Non-Line-of-Sight(NLOS)errors.In severe cases,NLOS errors can cause a ranging error of hundreds of meters,which has a substantial impact on the precision and dependability of GNSS positioning.To address this problem,we propose a reliable NLOS error identification method based on the Light Gradient Boosting Machine(LightGBM),which is driven by multiple features of GNSS signals.The sample data are first labeled using a fisheye camera to classify the signals from visible satellites as Line-of-Sight(LOS)or NLOS signals.We then analyzed the sample data to determine the correlation among multiple features,such as the signal-to-noise ratio,elevation angle,pseudorange consistency,phase consistency,Code Minus Carrier,and Multi-Path combined observations.Finally,we introduce the LightGBM model to establish an effective correlation between signal features and satellite visibility and adopt a multifeature-driven scheme to achieve reliable identification of NLOSs.The test results show that the proposed method is superior to other methods such as Extreme Gradient Boosting(XGBoost),in terms of accuracy and usability.The model demonstrates a potential classification accuracy of approximately 90%with minimal time consumption.Furthermore,the Standard Point Positioning results after excluding NLOSs show the Root Mean Squares are improved by 47.82%,56.68%,and 36.68%in the east,north,and up directions,respectively,and the overall positioning performance is significantly improved.展开更多
基金Graduate Innovation Ability Training Program of the Hebei Provincial Department of Education,2025(Project No.:CXZZSS2025095)。
文摘This paper designs and implements a single-camera 360°panoramic imaging system based on motor-driven fisheye rotation.The system utilizes a stepper motor for precise angular control,enabling the camera to rotate around its optical center to capture multi-view images,thereby avoiding the parallax and geometric mismatch problems inherent in traditional multi-camera configurations.To address the strong distortion characteristics of fisheye images,an equidistant projection model is adopted for distortion correction.On this basis,a brightness normalization method combining global linear brightness correction and local illumination compensation is proposed to enhance stitching consistency.By establishing a geometry model constrained by camera rotation and integrating cylindrical projection with cosine-weighted blending,the system achieves high-precision panoramic stitching and seamless visual transitions.
基金funded by the National Science Fund for Distinguished Young Scholars of China (Grant No.42425003)the National Natural Science Foundation of China (Grant Nos.42274034,42388102)+2 种基金the Major Program (JD)of Hubei Province (Grant No.2023BAA026)the Special Fund of Hubei Luojia Laboratory (Grant No.2201000038)the Special Fund of Wuhan University-Baidu Map Beidou Cooperative High-Precision Positioning Technology Joint Laboratory。
文摘In complicated urban environments,Global Navigation Satellite System(GNSS)signals are frequently affected by building reflection or refraction,resulting in Non-Line-of-Sight(NLOS)errors.In severe cases,NLOS errors can cause a ranging error of hundreds of meters,which has a substantial impact on the precision and dependability of GNSS positioning.To address this problem,we propose a reliable NLOS error identification method based on the Light Gradient Boosting Machine(LightGBM),which is driven by multiple features of GNSS signals.The sample data are first labeled using a fisheye camera to classify the signals from visible satellites as Line-of-Sight(LOS)or NLOS signals.We then analyzed the sample data to determine the correlation among multiple features,such as the signal-to-noise ratio,elevation angle,pseudorange consistency,phase consistency,Code Minus Carrier,and Multi-Path combined observations.Finally,we introduce the LightGBM model to establish an effective correlation between signal features and satellite visibility and adopt a multifeature-driven scheme to achieve reliable identification of NLOSs.The test results show that the proposed method is superior to other methods such as Extreme Gradient Boosting(XGBoost),in terms of accuracy and usability.The model demonstrates a potential classification accuracy of approximately 90%with minimal time consumption.Furthermore,the Standard Point Positioning results after excluding NLOSs show the Root Mean Squares are improved by 47.82%,56.68%,and 36.68%in the east,north,and up directions,respectively,and the overall positioning performance is significantly improved.
