On-Board Autonomous Task Planning Based on Ground-Object Properties

The Terrestrial Ecosystem Carbon Inventory Satellite (TECIS) “Goumang” is equipped with several payloads targeting worldwide or China’s domestic specific ground-objects, for example, the Aerosol Lidar working over lands in lighting and domestic area in shadow, the Directional Polarization Camera working in lighting area and the Fluorescence Spectral Imager aiming for lands in lighting. In order to improve the operation intelligence, a method of autonomous task planning for remote sensing satellites based on ground-object properties is proposed. The longitude and latitude of the nadir point after 90 min is extrapolated and forecasted firstly, and the lighting-shadow, land-ocean and domestic-overseas properties of the forecasted nadir point are obtained according to the on-board map and the solar elevation angle. Then the time table of every payload is generated based on the smoothed ground-object properties. Results of autonomous task planning for every payload can be created about one-revolution in advance.