Chen Ke-song

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

Simulation analysis of three-phase bridge rectifier circuit of aviation device

In recent years, with the upgrading of airborne device, most power source circuit of airborne devices use single-phase bridge and three-phase bridge uncontrolled rectifying circuit. Nonlinear characteristics of the rectifier circuit bring serious harmonic interference to the AC power system of the aircraft. This paper simulate and analyses the three-phase bridge circuit of airborne device power source with the help of Matlab, in order to help the governance of the aircraft AC power system harmonic.

Localized STAP approach with improved quiescent pattern control

The performance of adaptive signal processing in airborne phased radar is decreased greatly in the clutter environment. An improved quiescent pattern control approach is provided to solve this problem. The new approach uses a novel constraint which estimates the solution via Taylor series, where adaptive processing is non-orthogonal which is limited in localized processing region. The approach can mitigate clutter efficiently while maintain lower sidelobe. It has low sample support requirement, convenient implementation and low computation load. Performance analysis is carried out using simulated data. The results prove the effectiveness of the proposed approach in improving the reduced-rank STAP framework in beam-space.

SMT mixed soldering process designing parameters integrated analyzing platform

Mixed soldering is widely used in military, aerospace and medical electronics production, lead solder paste is used combined with lead-free components. It is necessary to choose proper soldering process design parameters to ensure the mixed solder joints high reliability. In this paper, the SMT mixed soldering process designing parameters integrated analyzing platform is developed, which can help the users to design the proper process parameters. Visual C++ secondary development technology is used to build the platform which contains series of steps in designing the mixed soldering parameters. Firstly, the solder joints three-dimensional shape model is established combined with the solder joints process designing parameters, the shape model is converted to the finite element model by the platform; Secondly, run the import file to analyzing the solder joints reliability by finite element method; Finally, neural networks and genetic algorithm is used for optimizing the reliability to get the best solder joints process designing parameters.

Krylov subspace method based on data preprocessing technology

Abstract The performance of adaptive beamforming techniques is limited by the nonhomogeneous clutter scenario. An augmented Krylov subspace method is proposed, which utilizes only a single snapshot of the data for adaptive processing. The novel algorithm puts together a data preprocessor and adaptive Krylov subspace algorithm, where the data preprocessor suppresses discrete interference and the adaptive Krylov subspace algorithm suppresses homogeneous clutter. The novel method uses a single snapshot of the data received by the array antenna to generate a cancellation matrix that does not contain the signal of interest (SOI) component, thus, it mitigates the problem of highly nonstationary clutter environment and it helps to operate in real-time. The benefit of not requiring the training data comes at the cost of a reduced degree of freedom (DOF) of the system. Simulation illustrates the effectiveness in clutter suppression and adaptive beamforming. The numeric results show good agreement with the proposed theorem.

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.