Research On The Application Of Compressed Sensing In MIMO Radar System

Multi-input Multi-output(MIMO)radar,as a new type of radar,has been deeply studied by many scholars at home and abroad.Compared with traditional phased array radar,MIMO radar has significant advantages in working mode,working efficiency,interference suppression and resolution.However,while gaining a lot of high performance,it has also brought tremendous pressure on the radar system in terms of system structure,data transmission,and signal processing.Compressed Sensing(CS)theory is a signal processing theory proposed for the high data rate and high sampling rate of signals in recent years.This theory can sample signal at a low rate and reconstruct it with a high probability.Applying the CS theory to MIMO radar system can not only process the system data at low speed in radar signal processing,make the data easier to transmit and store,but also simplify the design of the radar system structure in the radar antenna array and receiving channel.Therefore,in the context of MIMO radar combined with CS theory,this paper studies three aspects: using sparse sub-bands for ultra-wideband synthesis,using multiple beam method to scatter antenna array,and using Analog Information Converter(AIC)to design the receiving channels of MIMO radar system.The main work of the paper is summarized as follows:1.The basic theory of CS is introduced.In MIMO radar,the related theories and mathematical models of using sparse sub-bands for ultra-wideband synthesis,multiple beam method for sparse antenna array synthesis and AIC to design the receiving channels of MIMO radar system are described.2.The target imaging problems of ultra-wideband synthesized from multiple sparse sub-bands is studied.In the case where each sub-band is coherent,using the sparse characteristics of multiple sparse sub-bands relative to the full band,the low-band signal of 3GHz-3.7GHz and the high-band signal of 11.3GHz-12 GHz can be regarded as the sparse sampling of the full-band signal of 3GHz-12 GHz.The problem of wideband synthesis of high and low sub-bands can be transformed into the problem of reconstruction of sparse signals in CS.Then,a CS model for ultra-wideband synthesis by multiple sub-bands is established.High-resolution imaging of multiple scattering points in a stationary target is achieved.The experimental results are compared with traditional pulse-compressed images,and the performance of ultra-wideband synthetic images by CS is comprehensively analyzed and evaluated.3.The comprehensive problem of antenna array optimization by multi-beam joint convex optimization method is studied.According to the pattern envelope and beam scanning characteristics of a uniform array,a method of sparse array synthesis,a multi-beam joint convex optimization method,is proposed.This method is divided into two parts.In the first part,first,in the range of 0-60 degrees,combining the expected pattern envelopes of multiple differently directed beams with convex optimization algorithm,and then optimizing multiple parameters such as the number of elements,positions,and excitations in a uniform array.In the second part,first,fixed the number and position of the sparse array elements obtained by optimizing each beam pointing.Then,in the range of 0-60 degrees,the envelope of the desired pattern directed by multiple different beams is combined with a convex optimization algorithm to optimize the excitation of each array element of the sparse array.In both parts of this method,CS is used to sparsely sample,optimize,and reconstruct the desired pattern envelope,so that the sparse array method in this paper not only optimized the number,position,and excitation of array elements,but also realized beam scanning and multi-beam in a certain angle range.4.The problem of designing the receiving channel of MIMO radar system with piecewise AIC structure is studied.First,this paper uses Matlab/Simulink to model the piecewise AIC structure,and the specific design of each part of this system is given in detail.Then,Multi-harmonic signals are used to test the system's ability to process signals.The comparison of experimental results with pre-modulated and direct AIC structures reflects the advantages of the piecewise AIC structure in terms of data accuracy and hardware structure.Next,this piecewise AIC structure is applied to the receiving channel of a two-transmit and one-receive MIMO radar system,and this MIMO radar system is designed and modeled.Then,using linear frequency modulation(LFM)signals to simulate this MIMO radar system and test the performance of target detection and signal processing.Simulation results show that this MIMO radar system not only achieves the low-sampling processing of echo signals,but also realizes the range detection of stationary targets.It reflects the feasibility and advancement of applying this piecewise AIC structure to the receiving channel of MIMO radar.