Nanjing University of Aeronautics and Astronautics

Yang Huang

Qihui Wu

Kai Mao

Qiuming Zhu

Weizhi Zhong

Wei Wang

Jie Li

Xiaofei Zhang

Fuhui Zhou

Yiwei Lu

Lu Han

Shijin Zhao

Xuan Wu

Xiaofu Du

Tianchen Ruan

Wenqiang Liu

Yunpeng Bai

Xinyu Zhu

Miaomiao Dong

Junjie Zhang

Tianyu Hu

Tianxu Lan

Zhiren Gong

A three-dimensional (3D) spectrum situation completion method and device based on a generative adversarial network includes performing graying and coloring preprocessing based on incomplete 3D spectrum situations from historical or empirical spectrum data obtained by a UAV through sampling a target region, obtaining three-channel incomplete 3D spectrum situation maps displayed in colors, forming a training set based on the incomplete 3D spectrum situation maps; training the generative adversarial network based on the training set and obtaining a trained generator network in the generative adversarial network, performing graying and coloring preprocessing based on a measured incomplete 3D spectrum situation obtained by the UAV through sampling a specified measurement region, obtaining a three-channel measured incomplete 3D spectrum situation map displayed in colors, and using the measured incomplete 3D spectrum situation map as input data to the generator network to obtain a three-channel measured complete 3D spectrum situation map displayed in colors.

Three-dimensional spectrum situation completion method and device based on generative adversarial network

An air-ground joint trajectory planning and offloading scheduling method and system for distributed multiple objectives is provided. At the beginning of each timeslot, an unmanned aerial vehicle (UAV) selects a flight direction based on a total energy consumption of all devices and a total amount of unprocessed data of all the devices in the current system, and flies a fixed distance towards a certain direction. Before the UAV reaches a new location, each terrestrial user independently selects a task data offloading scheduling strategy based on the total energy consumption of all the devices and the total amount of the unprocessed data of all the devices in the current system. In order to improve an expected long-term average energy efficiency and data processing capability, the present disclosure also provides average feedbacks for an energy consumption and unprocessed data.

Air-ground joint trajectory planning and offloading scheduling method and system for distributed multiple objectives

A brain-inspired cognitive learning method can obtain good learning results in various environments and tasks by selecting the most suitable algorithm models and parameters based on the environments and tasks, and can correct wrong behavior. The framework includes four main modules: a cognitive feature extraction module, a cognitive control module, a learning network module, and a memory module. The memory module includes a data base, a cognitive case base, and an algorithm and hyper-parameter base, which store data of dynamic environments and tasks, cognitive cases, and concrete algorithms and hyper-parameter values, respectively. For dynamic environments and tasks, the most suitable algorithm model and hyper-parameter combination can be flexibly selected. In addition, with 'good money drives out bad', mislabeled data is corrected using correctly labeled data, to achieve robustness of training data.

Brain-inspired cognitive learning method

A method and a device for measuring a four-dimensional (4D) radiation pattern of an outdoor antenna based on an unmanned aerial vehicle (UAV) are provided. The device includes a measurement path planning unit, a UAV platform unit, a radiation signal acquisition unit, a data command processing unit, and a ground data processing unit. The measurement path planning unit, the radiation signal acquisition unit, and the data command processing unit each are suspended from the UAV platform unit by using a pod. The present disclosure applies to the radiation pattern measurement of an outdoor antenna.

Method and device for measuring four-dimensional (4D) radiation pattern of outdoor antenna based on unmanned aerial vehicle (UAV)

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Nanjing, China

Yang Huang