On-orbit Geometric Calibration of Linear Push-broom Optical Satellite Based on Sparse GCPs

The paper presents a geometric calibration method based on the sparse ground control points (GCPs), aiming to the linear push-broom optical satellite. This method can achieve the optimal estimate of internal and external parameters with two overlapped image pair along the charge-coupled device (CCD), and sparse GCPs in the image region, further get rid of the dependence on the expensive calibration site data. With the calibrated parameters, the line of sight (LOS) of all CCD detectors can be recovered. This paper firstly establishes the rigorous imaging model of linear push-broom optical satellite based on its imaging mechanism. And then the calibration model is constructed by improving the internal sensor model with a viewing-angle model after an analysis on systematic errors existing in the imaging model is performed. A step-wise solution is applied aiming to the optimal estimate of external and internal parameters. At last, we conduct a set of experiments on the ZY-3 NAD camera and verify the accuracy and effectiveness of the presented method by comparison.

Availability evaluation model for space-based optical aerial target detection system

For space-based optical detection systems,there is usually a difference between actual on-orbit operational performance and designed requirements based on fixed scenarios.To assess the availability of space-based optical detection systems in different backgrounds,the radiation characteristics of aerial targets have been simulated using body radiation and atmospheric transmission models.The background radiation characteristics were also statistically analyzed.Then,for the parameters of the fixed space-based optical detection system,the signal-to-clutter and availability were evaluated under different conditions.A linear relationship between the radiation intensity and the flight height of the target was obtained.For a space-based optical detection system,the analytical availability model was constructed.Finally,multiple groups of data under different simulation conditions were used to validate the universality and reliability of the model.This availability model could significantly reduce the time required to predict the availability of the space-based optical detection system.The model was also adopted to analyze the influence of flight height,mean and variance,and background clutter on the space-based optical detection availability.

Improved YOLOv3 Infrared Image Pedestrian Detection Algorithm

Security surveillance is widely used in daily life.For nighttime or complicated monitoring environments,this article proposes an infrared pedestrian monitoring based on YOLOv3.In the original YOLOv3 network structure,two aspects of optimization were made.One was to optimize the scale in the residual structure,and the rich features of the deconvolution layer were added to the original residual structure.The other was to use the DenseNet network to enhance the features.The optimization of fusion ability and delivery ability effectively improves the detection ability for small targets,and the pedestrian detection performance based on infrared images.After comparative testing,compared with YOLOv3,the overall mean average precision is improved by 4.39%to 78.86%.