With the rapid development of satellite technology, the demand on remote sensing applications has shifted from traditional static observation to dynamic monitoring. Current remote sensing satellites supporting moving target detection face challenges, such as the difficulties in extracting slow-moving targets, the limited observation coverage, and the difficulties of transmission and processing of large volumes of data. This paper proposes innovative approaches in camera imaging modes, data processing methods, and hardware architecture.(1)The design of a remote sensing camera with the dual-line array push-broom imaging mode is proposed, which allows for the acquisition of same-spectral dual-strip data with controllable time differences in a single imaging session; this breakthrough overcomes the challenge of observing large-scale moving targets under non-agile satellite conditions and provides a means to obtain"instantaneous change"information in the context of dynamic remote sensing.(2)The supporting onboard intelligent processing unit is developed independently, which is equipped with efficient onboard processing algorithms; through the design of high-performance parallel computing hardware-accelerated architecture, the hardware carrier of real-time remote sensing service in the dynamic remote sensing system is formed. The prototype based on the technology has been successfully launched aboard the MN200Sar-1 optical remote sensing satellite, positioning it as the first dedicated moving target detection satellite in the world. The on-orbit verification results show that the satellite is capable of detecting a wide range of moving targets within its sweeping field of view. It exhibits excellent detection performance for high-speed trains, vehicles, ships and other objects in motion. And the on-board processing unit meets the requirements for on-board processing applications in terms of time efficiency, energy utilization, and processing effectiveness. The related technologies and achievements hold significant theoretical and practical implications for various application domains, including intelligent transportation, disaster prevention and mitigation, and national security.

Cultural relics line graphic serves as a crucial form of traditional artifact information documentation, which is a simple and intuitive product with low cost of displaying compared with 3D models. Dimensionality reduction is undoubtedly necessary for line drawings. However, most existing methods for artifact drawing rely on the principles of orthographic projection that always cannot avoid angle occlusion and data overlapping while the surface of cultural relics is complex. Therefore, conformal mapping was introduced as a dimensionality reduction way to compensate for the limitation of orthographic projection. Based on the given criteria for assessing surface complexity, this paper proposed a three-dimensional feature guideline extraction method for complex cultural relic surfaces. A 2D and 3D combined factor that measured the importance of points on describing surface features, vertex weight, was designed. Then the selection threshold for feature guideline extraction was determined based on the differences between vertex weight and shape index distributions. The feasibility and stability were verified through experiments conducted on real cultural relic surface data. Results demonstrated the ability of the method to address the challenges associated with the automatic generation of line drawings for complex surfaces. The extraction method and the obtained results will be useful for line graphic drawing, displaying and propaganda of cultural relics.