Since traditional filter methods to solve Simultaneous Localization And Mapping (SLAM) problems will accumulate errors, a three-dimensional SLAM algorithm based on Bag-Of-Words (BOW) algorithm which can effectively solves the problem of accumulating errors was proposed. Compared to the common algorithms like random selection and k-Dimensional Tree (Kd-Tree), a tree structure visual bag of words loop detection algorithm was designed which could greatly increase the speed of similar scene detection. Firstly, a GPU based feature extraction algorithm was adopted. Through using cross matching and k-Nearest Neighbor (kNN) algorithm, robust inliers were got. Secondly, Random Sample Consensus Singular Value Decomposition (RANSAC SVD) algorithm was used to calculate the initial transformation between two frames. And then a Generalized-Iterative Closest Point (G-ICP) algorithm was used to optimize the transformation to get precise transformation. At last, incremental Smoothing And Mapping (iSAM) Graph optimization algorithm was used to calculate the camera pose and the point cloud map and trajectory were created. The test results on the standard dataset show that the algorithm can achieve good robustness and precision under complex environment.

To deal with high computing complexity and bad anti-CFO (anti-Carrier Frequency Offset) performance of conventional time synchronization algorithms for Time Division Long Term Evolution (TD-LTE) system, an improved algorithm based on Secondary Synchronization Signal (SSS) conjugate-symmetric in time domain was proposed in this paper. For the algorithm, SSS location was estimated as the peak of cross-correlation of received signal and its time reversal. And by combining SSS location with the detection of cell group ID, CP (Cyclic Prefix) type could also be judged. Analysis and simulation results demonstrate that the improved algorithm has low computing complexity, good performs on anti-CFO and better reliability compared with normal methods, especially, it also has good performs in multi-path channels. By applying to the third party TD-LTE UE detecting system, the algorithm is proved to be effective and feasible.