Development of Aerial-Ground Sensing Network: Architecture, Sensor Activation, and Spatial Path-Energy Optimization

The advent of autonomous navigation, positioning, and in general robotics technologies has enabled the maturity of small to miniature-sized unmanned aerial vehicles (UAVs; or colloquially called drones) and their wide use in engineering practice as a low-cost and effective geospatial remote sensing solution. Meanwhile, wireless sensing network technology (WSN) has also matured in recent years with many applications found in engineering practice. In this dissertation, a novel aerial ground wireless sensing network (AG-WSN) is developed, which is expected to transform a number of critical geospatial sensing and monitoring practices, such as precision agriculture, civil infrastructure protection, and disaster response. Towards the maximal energy efficiency, three research problems are concerned in this dissertation. First, a radio-frequency (RF) wake-up mechanism is investigated for aerial activation of ground sensors using a UAV platform. Second, the data transmission under wireless interference between the UAV and ground WSN is experimentally investigated, which suggests practical relations and parameters for aerial-ground communication configuration. Last, this dissertation theoretically explores and develops an optimization framework for UAV's aerial path planning when collecting ground-sensor data. An improved mixed-integer non-linear programming approach is proposed for solving the optimal spatial path-energy using the framework of the traveling-salesman problem with neighborhoods.

Name thesis:degree_name

Ph.D. (Doctor of Philosophy)

Level thesis:degree_level

Doctoral

Discipline thesis:degree_discipline

Electrical and Computer Engineering (UMKC)

Grantor dc:publisher

University of Missouri -- Kansas City

Year dc:date.issued

2019

Author dc:creator

• Chen, Jianfei

Advisor dc:contributor.advisor

• Chen, ZhiQiang

Language dc:language.iso

en_US

Handle dc:identifier.uri

https://hdl.handle.net/10355/68006

OAI identifier oai:identifier

oai:mospace.umsystem.edu:10355/68006