MIMO Radar Parameter Estimation Based On Jointly Sub-Nyquist Sampling In Space And Time Domains

With the widespread application of MIMO technology in the communication field,MIMO radar has become a hot spot in radar research in recent years.MIMO radar uses multiple antennas to transmit different waveforms at the same time and uses multiple antennas to receive reflected signals at the same time,thereby effectively improving target detection performance and radar anti-jamming capabilities.However,due to the use of multi-channel processing technology,MIMO radar inevitably increases system complexity,power consumption,and cost compared with traditional radar systems.Therefore,how to design an effective MIMO radar system and the corresponding signal processing algorithm is an important challenge for the MIMO radar research institute.This article mainly simplifies the design of MIMO radar system from the perspective of signal sampling theory,and develops the corresponding MIMO radar high-resolution target parameter estimation algorithm.In recent years,as the theory of compressed sensing has been proposed,new developments have also emerged in sampling theory.Applying compressed sensing theory to analog signal acquisition,people have proposed the concept of under-sampling(also known as "Sub-Nyquist(Sub-Nyquist)sampling").The under-sampling theory based on compressed sensing can use the structural information of the signal,such as sparsity,low-rank,etc.,to break the double relationship between signal bandwidth and sampling rate,and provide a theoretical basis for realizing low-speed sampling of broadband signals.This essay will study the design of undersampling MIMO radar under the framework of under-sampling theory,and propose a MIMO radar based on joint under-sampling in time domain and space domain.The under-sampled MIMO radar system can use a low-speed ADC and a small number of antennas to collect radar echo signals,while still maintaining the ability to obtain high-resolution target information.The main work of the essay is as follows:(1)The essay proposes a joint under-sampling scheme in the space-time domain to reduce the number of antennas and the complexity of spatial sampling,the MIMO radar based on space-time joint under-sampling can reduce the number of antennas and the sampling rate of ADC while keeping the space and time resolution unchanged,and reduce the system complexity and cost of the MIMO radar.(2)The essay proposes an algorithm based on the discrete grid method to realize the joint estimation of the target range-angle of the space-time domain under-sampling MIMO radar.This algorithm improves the traditional one-dimensional Orthogonal Matching Pursuit(OMP)algorithm into a two-dimensional OMP to realize the simultaneous restoration of distance and azimuth.Simulation experiments show that the algorithm can effectively achieve target parameter estimation based on space-time joint under-sampling data.(3)Aiming at the problem that the grid-based algorithm has errors when the target deviates from the grid,the essay proposes a grid-free target parameter estimation algorithm based on the two-dimensional atomic norm.This method improves the traditional atomic norm algorithm into a two-dimensional atomic norm algorithm to estimate the target parameter range and azimuth angle of the MIMO radar simultaneously.This algorithm takes advantage of the low-rank characteristics of the observed signal in MIMO radar,and converts the parameter estimation problem into a reconstruction problem of solving low-rank matrix,so as to realize the target parameter estimation of MIMO radar.Simulation experiments show that the algorithm can achieve high-resolution joint estimation of target distance and azimuth.