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UAVs have been widely used in the field of communication. Among them, micro-miniature multi-rotor UAVs are becoming more and more mature, but there are still insufficient endurance, lack of stability of system platform for communication payloads, and electromagnetic compatibility of equipment. The problem needs to be solved. This paper adopts the tethered multi-rotor UAV as the platform for the communication load, and uses the integrated design technology to complete the combination of the UAV platform and the RF load of the broadband wireless access system, thus developing the field environment adaptability. Analyze and organize applied research.

Image segmentation actually could be regarded as a computer vision pre-processing step of cloud computing and big data analysis. Active contour model is a new research direction for images segmentation in synthetic aperture radar(SAR) images. However, due to the SAR images have speckle noise and low signal-to-clutter ratio, active contour models cannot produce satisfied segmentation results. To solve these issues, active contours driven by visual saliency fitting energy is proposed in this paper. First, a saliency map is calculated by improved local contrast measure. Then, a visual saliency fitting energy is proposed based on saliency map and local binary fitting energy. The saliency map has a higher signal-to-clutter ratio and the local binary fitting energy is an active contour model that can effectively segment images with intensity inhomogeneity. In this way, the proposed method has a better segmentation result. The experiments on ship chips in SAR images demonstrate that the proposed method is robust to speckle noise and the segmentation result has good connectivity and integrity for entire ship targets.

The Hardware Trojans act as a new malicious attack for the underlying hardware, the research of method based on side-channel analysis become one of important contents for information security. But the method of Hardware Trojans detection based on side-channel analysis easily been affected by noise, and its detection model has low precision. This article uses the technology of BP neural network for Hardware Trojan detection, puts forward a method for the noise optimization by wavelet transform. We implant a hardware Trojan circuit occupied areas 0.54% in AES circuit, and make the realization of circuit and power analysis based on the FPGA platform. Experimental results show that the method of noise optimization by wavelet can eliminate the high frequency noise, improve the Hardware Trojan detection sensitivity based on neural network, and the detection sensitivity increased from 92.2% to 99.2%.