Li Zhenglin

Characteristic recognition of the fingerprints of wireless channel

In this paper, novel algorithms were applied to recognize the fingerprint characteristics of wireless channel. Firstly, Discrete Fourier transform were applied to acquire frequency domain results of measured date of a wireless communication channel. And then a feature extraction method using interpolation, normalization, extended maximum value filtering and closed operation was applied to realize the dimension reduction and get the fingerprints. Secondly, automatic recognization of the characteristics of different fingerprint images was discussed. It shows that KNN algorithm can effectively recognize different scenarios of wireless channels, while SVM algorithm cannot do well when the environment is complicated. Results show that the methods can satisfy the requirements of the identification of different communication channels.

Research on a New Algorithm of Traffic Sign Image Processing

In order to improve the effect of traffic sign image preprocessing, a preprocessing method using RGB(Red green blue) color space components is proposed. Firstly, the real image is divided into three components of RGB, and the components for processing are based on the the colors of traffic sign images collected. Then the image of each component is filtered, and next the image area of the traffic sign collected based on the colors is binarized and its contour is tracked to determine where it is. Finally, the area marked is collected. The simulation results show that this method can improve the speed and accuracy of traffic sign location and shape detection, and can acquire a good traffic sign contour image.

Enhancement of image edge definition by modified Quadtree sobel operator

This paper presents an image segmentation method based on modified Quadtree sobel operator which was applied to enhance the precision of defining the real edges of the digital images. After removes noise of the images via modified median filtering, and pre-segments the images according to their characteristics, quadtree operator merges different zones without noise by multiple-zone target segmentation algorithm. The segmented images has clear structure and reserves their characteristic information. Results show that the method can removes noise effectively and solves out the problem of inaccurate segmentation due to regional image overlapping.

Study of improved multiple signal classification algorithm based on coherent signal sources

The paper presents an improved multiple signal classification algorithm based on coherent signals sources to estimate the direction of the arrival coherent signals. In the process of implement the algorithm, data eigen values are first decomposed from the received signal sources, and then using the relationship between the signal subspace corresponding to big eigen value and the signal steering vector to achieve effective estimation of the direction via searching the multidimensional wave peak. The algorithm is suitable for any arrays and the dimension of the covariance matrix will not be decreased. Compared with other algorithms, improved multiple signal classification algorithm has the advantages of owing the ability of processing up to M (M-1) signals and handling more than one signals from one direction. Results show that the proposed algorithm is suitable for applied in applications such as seismic detection and mobile communication.