Daytime star images captured by dedicated near-space star sensors are characterized by short exposures,high noise,and low Signal-to-Noise Ratios(SNRs).Such imaging is also affected by atmospheric turbulence,causing op...Daytime star images captured by dedicated near-space star sensors are characterized by short exposures,high noise,and low Signal-to-Noise Ratios(SNRs).Such imaging is also affected by atmospheric turbulence,causing optical phenomena,such as scintillation,distortion,and jitter.This causes difficulty in recording high-precision star images during the daytime.This study proposes an adaptive star point extraction method based on dynamically predicting stars'positions.First,it predicts the approximate position of stars based on the star catalog,sensor attitude,observation time,and other information,improving the extraction accuracy.Second,it employs a regional SNR sorting method that adaptively selects star images with higher SNRs,suppressing the scintillation effect and enhancing the SNR of star images.Third,depending on the star's motion trajectory characteristics on the image plane,it utilizes the centroid smoothing method for extraction,thus overcoming the impact of star drift.Field experiments demonstrate that the proposed method can effectively overcome star scintillation,drift,and irregular imaging caused by atmospheric turbulence,achieving a 100%success rate.Moreover,the extraction accuracy improves by more than 80%compared to traditional adaptive methods,attaining a value of 0.05 pixels(0.5"),thereby meeting the requirements of daytime astronomical attitude determination and positioning.展开更多
A modified Fourier descriptor was presented. Information from a local space can be used more efficiently. After the boundary pixel set of an object was computed, centroid distance approach was used to compute shape si...A modified Fourier descriptor was presented. Information from a local space can be used more efficiently. After the boundary pixel set of an object was computed, centroid distance approach was used to compute shape signature in the local space. A pair of shape signature and boundary pixel gray was used as a point in a feature space. Then, Fourier transform was used for composition of point information in the feature space so that the shape features could be computed. It is proved theoretically that the shape features from modified Fourier descriptors are invariant to translation, rotation, scaling, and change of start point. It is also testified by measuring the retrieval performance of the systems that the shape features from modified Fourier oescriptors are more discriminative than those from other Fourier descriptors.展开更多
针对合作靶标特征点成像在大跨度动态测量中的特征提取精度下降、实时性不足问题,提出了一种融合帧间运动预测与改进亚像素边缘检测的自适应光斑质心提取方法。基于合作靶标测量运动连贯性特性,构建了动态感兴趣区域(Region of Interest...针对合作靶标特征点成像在大跨度动态测量中的特征提取精度下降、实时性不足问题,提出了一种融合帧间运动预测与改进亚像素边缘检测的自适应光斑质心提取方法。基于合作靶标测量运动连贯性特性,构建了动态感兴趣区域(Region of Interest,ROI)特征参数模型,以帧间运动预测实现ROI的快速定位,结合大律法阈值优化策略实现自适应Canny边缘检测,在提升计算效率的同时有效解决了不同测量距离下的降噪问题。然后,采用多方向Sobel算子与强度斜坡改进的Zernike矩相结合改进了边缘点定位算法,并基于高斯牛顿迭代改进鲁棒最小二乘圆拟合法,实现质心坐标计算。实验结果表明:在仿真测试中,本方法在不同噪声水平下的质心定位误差为0.001~0.025像素;实际测试中,ROI预测算法可满足加速度8.75 m/s^(2)以内的测量场景需求,10~30 m测量距离内的光斑重复性定位误差稳定在0.016~0.040像素,优于传统方法;光斑提取速度提升约75.5%,显著增强了系统的实时处理能力。本研究可为合作靶标的测量应用提供有效技术保障。展开更多
基金funded by the National Natural Science Foundation of China(Nos.42374011,42074013)through the Natural Science Foundation’s Outstanding Youth Fund Program of Henan Province,China(Nos.242300421150,242300421151)。
文摘Daytime star images captured by dedicated near-space star sensors are characterized by short exposures,high noise,and low Signal-to-Noise Ratios(SNRs).Such imaging is also affected by atmospheric turbulence,causing optical phenomena,such as scintillation,distortion,and jitter.This causes difficulty in recording high-precision star images during the daytime.This study proposes an adaptive star point extraction method based on dynamically predicting stars'positions.First,it predicts the approximate position of stars based on the star catalog,sensor attitude,observation time,and other information,improving the extraction accuracy.Second,it employs a regional SNR sorting method that adaptively selects star images with higher SNRs,suppressing the scintillation effect and enhancing the SNR of star images.Third,depending on the star's motion trajectory characteristics on the image plane,it utilizes the centroid smoothing method for extraction,thus overcoming the impact of star drift.Field experiments demonstrate that the proposed method can effectively overcome star scintillation,drift,and irregular imaging caused by atmospheric turbulence,achieving a 100%success rate.Moreover,the extraction accuracy improves by more than 80%compared to traditional adaptive methods,attaining a value of 0.05 pixels(0.5"),thereby meeting the requirements of daytime astronomical attitude determination and positioning.
基金Project(60873010)supported by the National Natural Science Foundation of ChinaProject supported by the Doctor Startup Foundation of Shenyang University of Technology,China
文摘A modified Fourier descriptor was presented. Information from a local space can be used more efficiently. After the boundary pixel set of an object was computed, centroid distance approach was used to compute shape signature in the local space. A pair of shape signature and boundary pixel gray was used as a point in a feature space. Then, Fourier transform was used for composition of point information in the feature space so that the shape features could be computed. It is proved theoretically that the shape features from modified Fourier descriptors are invariant to translation, rotation, scaling, and change of start point. It is also testified by measuring the retrieval performance of the systems that the shape features from modified Fourier oescriptors are more discriminative than those from other Fourier descriptors.
文摘针对合作靶标特征点成像在大跨度动态测量中的特征提取精度下降、实时性不足问题,提出了一种融合帧间运动预测与改进亚像素边缘检测的自适应光斑质心提取方法。基于合作靶标测量运动连贯性特性,构建了动态感兴趣区域(Region of Interest,ROI)特征参数模型,以帧间运动预测实现ROI的快速定位,结合大律法阈值优化策略实现自适应Canny边缘检测,在提升计算效率的同时有效解决了不同测量距离下的降噪问题。然后,采用多方向Sobel算子与强度斜坡改进的Zernike矩相结合改进了边缘点定位算法,并基于高斯牛顿迭代改进鲁棒最小二乘圆拟合法,实现质心坐标计算。实验结果表明:在仿真测试中,本方法在不同噪声水平下的质心定位误差为0.001~0.025像素;实际测试中,ROI预测算法可满足加速度8.75 m/s^(2)以内的测量场景需求,10~30 m测量距离内的光斑重复性定位误差稳定在0.016~0.040像素,优于传统方法;光斑提取速度提升约75.5%,显著增强了系统的实时处理能力。本研究可为合作靶标的测量应用提供有效技术保障。
