Abstracting underwater target azimuth tendency feature is a common method to identify underwater target dimension. The cross-spectrum method of splitting beam is often used to abstracting underwater target azimuth tendency feature. But when the SNR is very low, this method is inefficient. In this thesis, an improved algorithm is presented to abstract underwater target azimuth tendency feature which can be used in the low SNR. In the algorithm, the underwater target highlight structure feature is used, and by least square fitting twice the underwater target azimuth tendency feature will be finally obtained. The simulation experiment results show that the proposed algorithm can be used to abstract underwater target azimuth tendency feature even when the SNR is very low. The improved algorithm has made an important foundation for further studying the feature detection and recognition of an underwater target dimension.

With the distance between sonar system and target enlarging, the underwater target transits from near field to far field. Based on planar element scattering similarity, a novel algorithm is presented in this paper. In this thesis, an underwater target model is set up and meshed with triangular planar element by using the software of Ansys. Due to the sonar system is in far field to every planar element, the matrixes whose elements are the planar elements target strength can be calculated. In the course of an underwater target transits from near field to far field, the matrix whose elements are the planar elements target strength is becoming more and more similar to that in far field. Thus the correlation coefficient between the above two matrixes can be used to analyze the transition of an underwater target. Numerical calculation are presented, and the results show that the underwater target scattering characteristics in critical distance approximate the characteristics in far field, but the target strength which is calculated in critical distance is also should be modified little.