Research On MIMO Radar Imaging Algorithm Based On Array Design

Imaging techniques are becoming increasingly important in the field of military and civilian with social and scientific and technological developments.Optical imaging technology,infrared imaging technology,and radar imaging technology are the three main technical means in the field of imaging.Imaging radar due to work with all-time and all-weather,has become one of the indispensable tools to get important information for the situation.With the development of weapons and computers,the traditional radar imaging methods,such as SAR and ISAR,can not meet the demands of fast imaging.So it is urgent to develop a new system and new method to achieve fast high-resolution imaging of radar.In this paper,an optimization method of the layout of the transceiver array based on the MIMO radar system is proposed,and the imaging method based on compressed sensing theory is discussed in combination with array structure and target characteristics.According to whether the target has sparse structure and whether the array has block structure,this paper discusses the different performance effects in the general sparse theory and block sparse theory of compressed sensing imaging algorithm.Besides,we also carry out the corresponding analysis and simulation.The relationship among array structure,target characteristics,and sparse reconstruction algorithm is preliminarily verified.Based on the above description,the main work of this paper is as follows:1.An array optimization method based on the genetic algorithm is proposed.According to the requirements,the fitness function related to the number of array elements is designed,and the roulette method is used for selection and optimization.The actual array structure with the minimum number of array elements is directly given,which solves the problem that the traditional MIMO array design focuses on virtual array design and ignores the actual optimal array.With the potential of quadratic optimization,the MIMO array with the best pattern performance can be designed on the premise of the least number of elements.2.A compressed sensing imaging model based on a sparse array structure is derived.Under the assumption of uniform linear array,the compressed sensing imaging model of the array is derived.The structure of the nonuniform array is combined with the observation matrix in the form of a generalized unit array,and the compressed sensing imaging model of the nonuniform sparse array is derived.3.In this paper,the imaging algorithm of OMP and BOMP based on a nonuniform sparse array is proposed.According to the model of non-uniform array compressed sensing imaging,the effects of array structure and target characteristics on the OMP and BOMP imaging algorithms are analyzed.The target with sparse scattering points is more suitable for OMP compressed sensing imaging algorithm under a random array structure.For the target with sparse block structure,the BOMP algorithm under block structure array has a better imaging effect.