Research On Orthogonal Waveform And Array Optimization Design Of MIMO Radar

Multiple input multiple output(MIMO)radar refers to a radar system in which multiple transmitting antennas transmit signals,and each transmitting array element transmits different waveform signals and is received by multiple receiving antennas.This kind of waveform diversity of signal transmission makes MIMO radar have more advantages than common phased array radar in detection ability,anti-jamming ability,anti-interception ability,identification ability and parameter estimation ability,and has become a research hotspot in recent years.The transmitted signals of MIMO radar directly affect the detection ability,antiinterception ability and anti-interference ability of the system,so the orthogonal waveform optimization design of radar becomes an important part to improve the performance of the radar system.The array with low sidelobe is very important for improving the recognition ability of MIMO radar system,so the sparse array optimization design is very important for improving identification ability and the parameter estimation ability of MIMO radar system.The centralized MIMO radar is used as the platform in this paper.The MIMO radar orthogonal waveform optimization design,Sparse Linear Array(SLA)optimization design,Direction of Arrival(DOA)estimation and other related problems were studied.The specific problems are as follows:Firstly,aiming at the orthogonality optimization of phase coded signals transmitted by centralized MIMO radar,an improved Algorithm based on Dragonfly Algorithm(DA)was proposed to study the orthogonality optimization of phase coded signals.The sum of Autocorrelation Sidelobe Peak(ASP)level and Cross-correlation Peak(CP)level and autocorrelation integrating sidelobe level is taken as the objective function.The state transition operator is added into the process of exploration and optimization of the algorithm and the process of development and optimization to balance the global exploration ability and local development ability of the algorithm in the iterative process;a cross-mutation strategy based on individual information is adopted to avoid premature convergence in the late iteration period;the original transition optimization process of the algorithm is improved,so that the algorithm can maintain the diversity of the population and accelerate the convergence speed during the transition process.The optimized phase coded signal has lower autocorrelation peak sidelobe level and cross-correlation peak sidelobe level,that is,the signal has relative orthogonality,which effectively improves the detection ability of dim target and the ability of anti-interception and anti-interference of MIMO radar system.Secondly,an improved Algorithm based on Harris Eagle Algorithm(HEA)is proposed to solve the sparse array optimization problem of centralized MIMO radar.The sidelobe value of the array equivalent virtual transmitting and receiving beam direction pattern was taken as the optimization objective function.The local search ability of Harris Eagle algorithm is improved by integrating the barycentric neighborhood search and state transition operator;the horntail search strategy is added in the iterative process,so that the algorithm always maintains a high population diversity in the iterative process,and improves the convergence speed and accuracy of the algorithm.The improved Harris Eagle algorithm is used to optimize the position of the element,and the direction diagram of the virtual transceiver beam of the sparse array are obtained.The recognition ability of the MIMO radar system is improved effectively.The optimized sparse array is simulated by estimation of the DOA without coupling and with coupling.Through the simulation results,it is found that the optimized sparse array can successfully identify most targets no matter the source is uniformly distributed or randomly distributed,and has a better DOA estimation ability than the Uniform Linear Array(ULA);the simulation results show that with the increase of signal-to-noise ratio,the optimized sparse array has obvious advantages in performance,and its root-mean-square error is much lower than that of uniform array.Compared with uniform array,the sparse MIMO array optimized in this paper has stronger DOA estimation ability and stable performance,and its root-mean-square error does not fluctuate greatly with the change of signal-to-noise ratio.The parameter estimation ability of MIMO radar system is improved effectively.