In order to solve the problem of low matching quality of the traditional feature extraction and matching algorithm in Unmanned Aerial Vehicle （UAV） visual localization， a new image matching algorithm based on transmission tower area extraction was proposed. Firstly， the image was divided into several overlapping grid areas， and the feature points were extracted by a two-layer pyramid structure for each area to ensure the uniform distribution of feature points. Then， the Line Segment Detector （LSD） algorithm was used to extract the lines in the images， the transmission tower support areas were extracted on the basis of special structure of transmission tower. Finally， the feature points in the transmission tower areas and the background areas were matched respectively in continuous images to further estimate the camera motion. In the rotation and translation estimation experiment， compared with the traditional Oriented Features from Accelerated Segment Test（FAST） and Rotated Binary Robust Independent Elementary Features （BRIEF） （ORB） feature extraction and matching algorithm， the proposed algorithm has the feature matching accuracy improved by 10.1 percentage points， the mean value of relative pose error reduced by 0.049. In the UAV inspection experiment， the relative error of the UAV trajectory estimation by using the proposed algorithm is 2.89%， which indicates that the proposed algorithm can achieve the robust and accurate estimation of the UAV’s pose during the real-time flying around the tower.

Based on the study of the application layer of Dedicated Short Range Communication (DSRC) protocol stack, as for the ASN.1 PER encoding and decoding module, a framework for encoding and decoding was designed and implemented, which included ASN.1 mapping rules, a general procedure for encoding and decoding, and a memory management method specifically designed for small devices. The framework is of good generality because of well-organized modules. The test results show that the framework has good performance, and it meets the real-time requirement of the protocol.

According to 6LowPAN drafts, an ultra-lightweight IPv6 protocol stack was greatly tailored for wireless sensor networks by studying the tree topology of wireless sensor network, adaptation functions and IPv6 protocols. The design has dramatically reduced the codes space and the overheads of the communication among IPv6 protocols, and it meets the constraints of low energy consumption and limited processing power in wireless sensor network.