Joint Radar And Communication Technology Research On Enhancing Vehicle To Vehicle Interconnected Perception

With the increase of vehicles on the road,road safety has gradually been taken seriously.The use of radar and communication technology to make vehicles have early warning capability and communicate with other vehicles or roadside facilities has resulted in proposing Intelligent Traffic System(ITS).The system requires that future smart vehicles must have both wireless communication and radar sensing capabilities.These two functions can be implemented on two separate platforms,but due to the limited space of the vehicle itself,if the two platforms are used separately,the implementation becomes very cumbersome.However,if two kinds of functions are concentrated in a transceiver platform,there are many other advantages,such as low cost,multi-function,low power consumption.Therefore,it is an important measure to realize wireless communication and radar sensing through a system.This thesis analyzes the research status of joint radar and communication system at home and abroad and finds that Orthogonal Frequency Division Multiplexing(OFDM)technology can be used as the key to the fusion of communication system and radar system.Though OFDM based joint radar and communication signal has good ambiguity function,communication performance and the possibility of distance and velocity estimation,in order to apply to the time-frequency dual-selection channel in the road traffic scene,the FRFT-OFDM joint radar and communication signal based on fractional Fourier transform is applied to enhance the vehicle-to-vehicle interconnection.Firstly,the fractional Fourier transform and its discrete algorithm are introduced.The structure,characteristics and implementation of the joint radar and communication system based on FRFT-OFDM are introduced.The basic principle and implementation method of how the integrated system effectively combating time-frequency dual-selection channels are described.In order to eliminate the influence of communication symbols on the ambiguity function,the mean wide-band ambiguity function is proposed and the mean wide-band ambiguity function of FRFT-OFDM based joint radar and communication signal is derived.Compared with the OFDM based joint radar and communication signal,the results show that the former has better distance and velocity resolution and anti-interference ability.In addition,the communication error rate of the two integrated systems is compared under different maximum Doppler frequency and modulation mode.Through the analysis of the simulation results,the bit error rate of these two systems is not much different,but the FRFT-OFDM based joint radar and communication signal is slightly improved.The above preliminary analysis results show that the joint system based on FRFT-OFDM has the possibility to enhance the interconnection of vehicle and vehicle and has better performance.It also introduces how to effectively utilize the target motion information obtained by the joint system.Moreover,integrated system super-resolution distance and velocity estimation algorithm based on two-dimensional multiple signal classification(MUSIC)is proposed to obtain basic motion information of targets.Firstly,the signal form of the transmitter and the receiver of the FRFT-OFDM based joint system is analyzed.The effect of the uncertain communication data is eliminated by the operation of point division.And then the matrix obtained through subsequent processing and the array flow pattern of L type array has a similar structure.With reference to two-dimensional DOA estimation algorithm based on MUSIC,the distance and velocity estimation algorithm of the integrated system is proposed and designed.In the simulation,multi targets with different distance and speed conditions are set.The ability of distance and velocity estimation and distinguishing targets are observed under different SNR.The results show that the algorithm can completely distinguish multi targets under the appropriate SNR.The algorithm has high detection accuracy and meets the accuracy requirements of distance and velocity estimation under road traffic scenarios.