Analysis On Detection And Estimation Of Cooperative MIMO Radar And MIMO Communications System

With the large-scale commercial deployment of the 5G communications,the global industry has begun to explore the next generation of mobile communications(6G)to realize the interconnection of all things to the intelligent connection of all things.In the future,the society will become increasingly high-end and intelligent.The integration of communications and radar,as one of the key technologies to realize 6G,has also been widely concerned by academic and industrial circles.The integrated radar and communications system can be divided into dual function radar and communications system and co-existing radar and communications system.In the dual function integrated system,the radar and communications system share the same hardware platform on the receiver and/or transmitter to achieve radar and communications functions.In the co-existing integrated system,the hardware and software platforms of radar and communication systems are separate but share limited spectrum and/or other resources.In the traditional co-existing integrated designs,the radar and communications systems mostly regard the signal of the other system as interference.Based on the traditional co-existing integrated system,the cooperative integrated multiple-input multiple-output(MIMO)radar and communications system is proposed in this dissertation,using MIMO technology and considering proper cooperation between two systems to improve the integrated system’s performance.The following are the primary contributions and innovations :(1)For the special case of passive MIMO radar that completely relies on communications signals to detect targets,the influence of different degrees of cooperation between the radar and the communications system on the performance of radar parameter estimation is studied.Three scenarios are mainly considered: communications sharing signal form with radar,not sharing any signal information,and sharing the statistical characteristics of the signal.The maximum likelihood(ML)estimation and the corresponding Cramer-Rao bound(CRB)of radar parameters in each scenario are given,and the estimated performance of each scenario is compared,and the influence of direct path signal on estimation performance is analyzed.(2)Different from existing co-existing integrated studies which regard the signals of the other system as interference,this dissertation studies the cooperative co-existing MIMO radar and communications system and proposes the definition of hybrid active and passive MIMO radar and radar-assisted communications.The target detection and localization performance of the hybrid active and passive MIMO radar and mutual information(MI)of the radar-assisted MIMO communications are studied,and the joint design of the integrated system is analyzed based on the obtained radar performance and communications performance.(3)Consider the possible cost limitation of radar receiving equipment in scenarios such as 6G communications or intelligent connection of everything.To make fully use of the information,each local receiver sends the data to the fusion center through a wireless communications backhaul for signal processing.The local receiver usually adopts quantization to save the cost and reduce the burden of communications,which is called cloud radar in this dissertation.The Gaussian approximation of quantization output is proposed to address the difficulty of obtaining the closed-form performance expressions from discrete quantized output.The target detection performance of the cloud MIMO radar system based on quantized data is discussed using Gaussian quantization output approximation.Three methods are proposed based on different quantization strategies and different fusion strategies: quantize local test statistics which are linearly fused(QTLF),quantize local test statistics which are optimally fused(QTOF),and quantize local received signals which are optimally fused(QROF).Firstly,the quantizer output is modeled as discrete random variable and the detection performance of each method is analyzed directly.The output of quantizer is then approximated,a closed-form expression of detection probability is obtained,and the performance of the three methods is compared to guide the system design.Finally,the performance difference between cooperative system and non-cooperative system is investigated.(4)The radar parameter estimation of the cloud MIMO system is discussed.Firstly,the direct analysis and Gaussian quantization output approximation of received signals based on quantization are used to obtain the ML estimation of location and velocity,as well as the approximation CRBs.In order to reduce the communications burden,a new method based on quantized time delay is proposed.In the local receiver,the time delay is estimated and the quantized time delay estimate is transmitted to the fusion center.The target position’s ML estimation and CRB for the quantization-based time delay estimation are obtained.The performance of the two methods is analyzed in simulation,and the two methods based on received signal quantization and time delay quantization are compared.