Han Chun-lin

Sidelobe Reduction of Linear Nonuniformly Spaced Arrays

This paper describes a modified genetic algorithm (MGA) for optimizing the performance of linear sparse arrays with a fixed current distribution. Under the design constraints of the number of elements, the aperture and the minimum element spacing, the MGA has been utilized to optimize the element position to reduce the peak sidelobe level (PSLL) of the sparse arrays. Unlike standard GA using unalterable corresponding relationship between the gene variables and their coding, the MGA employs the coding resetting of gene variables to avoid infeasible solution throughout the GA evolutionary process. And the proposed approach has reduced the size of the searching area of the GA by means of indirect description of individuals. The process of MGA and the simulated results confirming the great efficiency of this algorithm are provided in this paper

A new method for edge detection of SAR image

A combined method for edge detection of SAR images is put forward in this paper. This method is composed of the wavelet transform, fuzzy median filter, adaptive thresholding and differential gradient operator. In using the fuzzy median filter, this paper gives a new method for adaptively selecting the factors of the fuzzy median filter. The experimental results show the effectiveness and stability of this method.

The application and implementation of ACMLD-CFAR in monitoring receiver software

Under nonhomogeneous environments, the monitoring detector using fixed threshold method of signal detecting to capture blind signal can lead to large false-alarm probability. In view of the problem, combining the thoughts of radar constant false alarm probability, Automatic Censored Mean Level Detector-Constant False Alarm Rate (ACMLD-CFAR) method is proposed to detect signal. The suggested method, compared with the existing method, have obvious advantages. The method can capture burst signal without prior knowledge of the background, whats more it is easy to be implemented in software, and in the environment with obvious interference it can reduce the false alarm probability obviously.

Optimization of Sparse Plane Arrays Using an Improved Genetic Algorithm

For the element position synthesis of sparse rectangular plane arrays with the design constraints of the number of elements, the aperture and the minimum element spacing, an improved genetic algorithm (IGA) based on chromosome element resetting is presented in this paper. Compared with the synthesis method of thinned arrays, this new approach could exploit more degree of freedom of elements to control the characters of the sparse arrays. When the aperture, the number of elements and the minimum element spacing are fixed identical, the new approach can make the sparse plane array produce lower peak sidelobe level (PSLL). The simulated results show that the fitness function value of thinned plane arrays with 108 elements mentioned by Haupt can reduce 5.626dB when the minimum element spacing of half wavelength was introduced into the optimization. And as well, the great efficiency and the robustness of IGA are shown in this paper.