Research On Waveform Design And Processing Method For OFDM-Based Integration Of Radar And Communication

Integration of radar and communication(IRC)uses one system to realize radar detection and wireless communication functions simultaneously,which is beneficial to improve the hardware and spectrum utilization.Orthogonal frequency division multiplexing(OFDM)signal has many excellent characteristics and is adopted in radar and communication systems.This thesis focuses on waveform design and processing method for OFDM-based integration of radar and communication.The main work is as follows:1.This paper first proposes a weighted preprocessing integrated waveform optimization method to solve the disadvantages of the high sidelobes of the ambiguity function of the direct information modulation integrated signal and the large bandwidth of the spread spectrum information modulation integrated signal.The ambiguity function and correlation function of the multi-symbol OFDM integrated signal are analyzed,and the correlation characteristics of the original sequence are improved by randomly selecting the weighted coefficients,so as to optimize the peak sidelobes ratio performance of its ambiguity function.Simulation results show that the proposed integrated waveform has lower peak sidelobes ratio than the direct information modulation integrated signal and has a smaller bandwidth than the spread spectrum information modulation integrated signal.Its communication rate and bit error rate meet the communication requirements,which makes it suitable for the integration of radar and communication.2.In the research content of integrated signal echo processing method,aiming at low speed target echo signal,this thesis proposes a joint range-velocity estimation method based on multi-symbol OFDM integrated echo signal.A two-step parameters estimation method is proposed,where estimating the signal parameters via the rotational invariance technique(ESPRIT)performs rough estimation and weighted subspace fitting(WSF)performs fine estimation.We first establish the integrated echo signal receiving model based on communication information division.The ESPRIT method based on double Vandermonde structure array manifold is adopted for rough estimation.Its estimation error is relatively large,but the computational complexity is low.The WSF method based on the alternating projection algorithm is introduced for fine estimation to reduce the estimation error.It uses the results of rough estimation and reduces the computational cost.Simulation results show that the proposed method improves the estimation accuracy while reducing the computational complexity.3.In highspeed scenarios,the multi-symbol OFDM-based integrated echo signal needs to consider the intra-symbol and inter-subcarrier Doppler effects.This paper first establishes an integrated echo signal receiving model including the intra-symbol and inter-subcarrier Doppler effects.On this basis,a two-step joint range-velocity estimation method using ESPRIT method for rough estimation and least square weighted(LSW)method for fine estimation is proposed.The extraction matrix of the ESPRIT algorithm is improved so that it can be applied to highspeed target echo signal,but its estimation error is high.The alternating projection LSW algorithm is introduced to perform fine estimation on the estimation results of the first step,so as to improve the estimation accuracy.Simulation results prove the superiority of the proposed method.4.In highspeed scenarios,the multi-symbol OFDM-based integrated echo signal can be fitted better by approximating the items in the receiving signal model as little as possible.This paper first builds an integrated echo signal receiving model containing all terms.Using this model,a maximum likelihood(ML)method for range and velocity independent estimation is proposed.The proposed method takes the partial derivative of the ML estimation error with respect to the range term and replaces it.The estimated velocity is substituted into the error to estimate the range of the target.Because the spectral peak is searched in the velocity dimension and range dimension,the search space is greatly reduced compared with that in the range-velocity dimension.Theoretical analysis and simulation results verify the effectiveness of the proposed method.