Decoherent DOA Estimation In Integrated Car Radar Communication System

Intelligent driving promotes the development of the Intelligent Transportation System(ITS).vehicle in the process of driving,use vehicle-mounted radar signal integration,to estimate the Angle of target signal DOA(Direction of concatenated,DOA)joint range and speed of the vehicle information can function the positioning of the vehicles in the network environment.However,due to the multipath interference during the signal propagation of the smart car or the use of the same frequency point for vehicle and obstacle detection,it will cause the receiver to deal with the coherent signal.In order to eliminate the negative impact of the inter-vehicle coherent signal on DOA estimation,a decoherent DOA estimation algorithm based on the integration of the vehicle-borne radar communication is proposed;Focusing on the problems of DOA estimation under the car networking application scenario,this paper proposes a one-dimensional and two-dimensional DOA decoherence estimation method for car networking environment.The specific research content is as follows:(1)Aiming at the system model of car-borne radar communication integration in the car networking application scenario,a case study of one-dimensional DOA estimation is proposed.The traditional one-dimensional DOA estimation algorithm for vehicle networking has poor robustness under low application conditions such as low signal-to-noise ratio,small snapshots,and non-equal multi-target due to the harsh conditions.At the same time,it is impossible to eliminate the signal coherence in the car network.Therefore,a subspace projection synthesis spectral decoherence algorithm suitable for IOV scenes is studied.This algorithm not only ensures the accuracy of and robustness of the algorithm under low SNR and low angle conditions.The effectiveness of the proposed method is analyzed throuth simulation experiments.(2)Vehicles in the car networking environment are not always at the same level.Therefore,the study of two-dimensional DOA estimation is very important for smart driving.Because the traditional two-dimensional DOA estimation algorithm needs complicated peak searching process or additional pairing of pitch angle and azimuth angle,it takes a long time,which seriously affects the real-time detection requirements of the car network.In this paper,a novel two-dimensional DOA estimation algorithm is proposed,which enhances the rigor of the algorithm in the dimension reduction process,reduces the search complexity of the algorithm,and also eliminates the interference of the coherent signal to the DOA estimation.The obtained pitch angle is Azimuth is a one-to-one correspondence,avoiding repeated angle pairing processes.The experimental analysis shows that the proposed algorithm can eliminate the coherence of the signal,has higher estimation accuracy and resolution,and also has better robustness.