Multi-Sparse Array Optimization Configuration Method For Imaging Tasks

With the development of modern aircraft technology,high resolution radar imaging technology has become an important development direction.The high resolution of radar imaging depends on the large imaging aperture,and the traditional real aperture radar is difficult to meet the requirements.However,with the development of sparse array technology,the high resolution imaging of real aperture radar also becomes possible.Compared with the traditional uniformly densely distributed array,a larger aperture can be obtained by using the same number of elements,and its position restriction on the array element is less,and the degree of freedom and array damage resistance are high.In addition,through multi-array joint imaging,the utilization rate of system resources can be improved,the imaging coverage and working performance can be enhanced,and the spatial diversity can be fully utilized,and the negative impact of different radar crosssectional areas at different angles can be reduced.In this context,aiming at the multi-sparse array joint imaging problem,this paper focuses on the optimization scheduling method of system resources from two levels of element selection and target allocation.The main research results are as follows:1.Aiming at the multi-region imaging scenario of single sparse array,an optimal allocation model of multi-region imaging resources was established,and an array optimization selection algorithm based on genetic algorithm was proposed.The simulation shows that the array can effectively improve the imaging performance of each object under the condition of limited number of arrays.2.Aiming at the multi-sparse array multi-region joint imaging scenario,a two-step real-time resource scheduling algorithm with low complexity was proposed.The multiarray and multi-region imaging resource scheduling problem was decomposed into an independent task optimization assignment and an array optimization selection problem.By reducing the coupling degree between arrays,the resource allocation problem was simplified and the optimization difficulty was reduced.3.The threat degree algorithm is introduced as the performance evaluation index,a single-index constrained task allocation model is constructed,and an improved Hungarian algorithm is proposed,which can effectively obtain the optimal task allocation scheme.4.Based on sparse array imaging characteristics,the concept of multi-target array total perspective was proposed.Combined with threat degree algorithm,a dualindex constrained task optimization allocation model was constructed,and a task optimization allocation algorithm based on non-dominated sorting genetic algorithms II(NSGA-II)is proposed,which can effectively obtain the Pareto approximate optimal solution.