Study On Height Estimation Technologies Of Low Angle Target For Digital Array Radar

The problem of low elevation angle estimation can be equivalent to an elevation angle estimation problem,which is one of the classic problems in the radar field.The difficulty is that the direct signal and multipath signal received by the radar cannot be separated in the time,Doppler,and space domain.The system resources of traditional radar are limited,and low elevation angle estimation performance is far from meeting military needs.Digital array radar has more advantages over traditional radar,providing new ways for the solution of many problems in the radar field.However,the system has problems such as more complex and large calculations.Based on the digital array radar,this dissertation conducts research on the two key issues of improvement accuracy and reduction of calculation in low elevation angle estimation.The main contributions of this dissertation are shown as follows:(1)For the frequency diversity radar,the echoes of different frames have fluctuation,so the signal-to-noise ratio(SNR)of different frames is different,resulting different angle estimation accuracy with the echoes of different frames.Therefore,based on the good performance of the refined maximum likelihood(RML)algorithm,this dissertation proposes an optimal fusion frequency diversity RML algorithm.The algorithm constructs an optimization problem,which minimizes the mean square error(MSE)of angle estimation.Thereby,the optimal weight at different frequency points is obtained for fusing the angle estimation.Through theoretical analysis and simulation,the proposed algorithm can improve the accuracy of angle estimation effectively.(2)When the degree of fluctuations of the reflection surface is large,the composition of multipath signals is difficult to determine,and the actual radar antenna height and reflection coefficient are difficult to obtain directly,which will cause the estimation performance of conventional algorithms to be seriously reduced.To this end,this dissertation conducts research on the environment of different degrees of fluctuations.For the undulating surface with a certain rule,we first obtain effective terrain height information,and then corrects the reflection coefficient and antenna height,and then uses the RML algorithm for elevation estimation.For the large undulating surface without a certain rule,this dissertation proposes a target elevation angle and multipath phase joint estimation algorithm.The algorithm first uses the characteristics of the target echo data to analyze the composition of received signals,and then alternately optimizes the target elevation angle and multipath phase.These two methods have different applications,but both can effectively improve the stable performance of elevation estimation.(3)For massive arrays,the amount of data transmission,storage and computation of radar is very large,and the conventional methods cannot meet engineering needs.The processing in beamspace can reduce data transmission,storage,and computation on the premise of ensuring estimation accuracy,which is convenient for engineering implementation.However,the existing research does not apply difference beams in the super-resolution method.To this end,this dissertation proposes two ML algorithms based on sum and difference beams.These two algorithms first construct the beamformer that includes the sum and difference beams and convert the target data to the beamspace,and then perform elevation estimation by ML or RML in beamspace.Each beamformer constructed by the algorithm includes 2 or 3 sum beams and 2 or 3 difference beams,and the number and directions of beams can be adjusted according to the application.The results of computer simulation and real data processing demonstrate the effectiveness of the proposed algorithms.(4)The processing in beamspace does not affect the multipath phase,and the multipath phase is a function of the target elevation angle.Based on this feature,this dissertation proposes a high-accuracy elevation angle estimation algorithm without searching.The algorithm first uses three-dimensional beamspace data to solve the multipath phase problem without searching,and then use the multipath phase to directly derive the target elevation angle.Therefore,the proposed algorithm has very low computation.Computer simulation and real data processing results show that under the same prior information conditions,the estimation accuracy of the algorithm is basically the same as the estimation accuracy of the search-based algorithm,which is very suitable for engineering applications.(5)This dissertation conducts low elevation estimation method in beamspace for the multiple input multiple output(MIMO)radar.MIMO radar can perform transmitting beamforming and receiving beamforming at the receiving side,which can improve angle resolution and estimation accuracy.Thus,this dissertation proposes a beamspace MIMO radar refined maximum likelihood algorithm.The algorithm first constructs the transmitting and the receiving beamformer,and then converts the MIMO radar target data to beamspace,and then uses the RML algorithm to complete the elevation angle estimation in beamspace.The simulation results show that compared with the RML algorithm in element space,the estimation accuracy of the proposed algorithm is basically no loss,and the computation of the algorithm is significantly reduced.(6)This dissertation discusses beamspace target height estimation for bistatic MIMO radar.For bistatic MIMO radar,the transmitter and the receiver sides are placed in different places.The target height needs to be estimated at two sides,which leads to a significant increase in computation.However,current literature has not yet considered beamspace target height estimation for bistatic MIMO radar.Although target height estimation algorithms can be directly applied to bistatic MIMO radar after minor modifications,such a direct application does not afford optimum performance.Therefore,we develop a threedimensional beamspace maximum likelihood data fusion(3D-BMLF)algorithm appropriate for the target height estimation algorithm of bistatic MIMO radar.The 3D-BMLF algorithm first converts target signals to the 3D beamspace,separates the transmitter and the receiver signals,and obtains two closed-form solutions of target height using the ML algorithm without searching.Finally,the proposed method fuses the two closed-form solutions by minimizing the MSE of estimation.The 3D-BMLF algorithm has a very low computational burden and good estimation accuracy.The computational complexity analysis and simulation results demonstrate the suitability of the 3D-BMLF algorithm for engineering applications.(7)When MIMO radar’s reflection surface has a large degree of fluctuations,the composition of multipath signals is difficult to determine,and the estimation performance of conventional algorithms will be severely reduced.Thus,this dissertation discusses the issue of low-angle estimation in MIMO radar and develops a beamspace scene classification(BSC)algorithm to enhance the performance of low-angle estimation in MIMO radar.The proposed algorithm solves an initial angle estimate and the multipath coefficient estimate using the 3D beamspace data,and further constructs the beamspace data required for transmitter and the receiver sides to reduce the data dimensions.It is additionally used to provide three estimation schemes with closed-form solutions for three multipath scenes.Finally,it fuses the estimates of the two sides by minimizing the MSE of estimation.The computational complexity analysis and simulation results show that the BSC algorithm has high estimation accuracy and strong robustness while requiring few processing resources.