Information collection and transmission control system for unmanned aerial vehicle

Abstract

The invention discloses an information collection and transmission control system for an unmanned aerial vehicle. The system comprises a DSP powered by a power supply module. The DSP is separately connected to an inertial sensor, a gas pressure altitude sensor, a GSP module, an ultrasonic sensor, an airborne remote sensing facility and an electronic speed regulator. The gas pressure altitude sensor and the GPS module are connected to the DSP after comparison, the DSP performs wireless communication connection with an information processing system of a ground station through digital microwave transmission, the information processing system is connected to an information display interface and an operating terminal, the information processing system can transmit the collected images and the data information of information data, and also can process an operating command of the operating terminal. By adopting the structure and integrating technologies of computer network communication and wireless communication and the like, multi-aspect functions such as traffic management, big data statistics, disaster prevention pre-warning, geographical mapping, meteorological observation, travelling navigation, real-time monitoring and the like can be achieved.

Description

technical field

[0001] The invention relates to an unmanned aerial vehicle control system, in particular to an unmanned aerial vehicle information collection and transmission control system. Background technique

[0002] With the development of society, it has become an important task for people to effectively analyze the information of urban areas (disaster prevention and early warning, geographical surveying and mapping, meteorological observation, and road navigation). Analyzing various data is the key to solving urban security problems in major cities in the future. An important strategy of governance. In the existing technology, various data (such as the analysis of the current traffic conditions) are usually aggregated and compared by some artificial statistical methods. For example, the traffic data is predicted through the comparison results. The existing This method is relatively backward, single, requires a lot of manpower and material resources, and is not accurat...

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