Research On Spatial Digital Domain Self Interference Cancellation Technique For Acoustic Decoys

In recent years,with the continuous development of underwater acoustic technology,acoustic decoys occupy an important position in the field of underwater acoustic countermeasures.In order to make the acoustic decoy can realize intelligent and cooperative operation,it will adopt the system of transceiver split to realize receiving signal and transmitting signal at the same time.In this system,the correct reception of the target signal is the primary task,which is a prerequisite for the realization of underwater acoustic communication and underwater acoustic countermeasure technology.However,due to simultaneous transceiver and transmitter,the receiver will inevitably receive the local transmission leakage signal.In this paper,in order to complete the cancellation of local self-interference signals for the above application scenario,interference suppression techniques based on array signal processing techniques and digital domain self-interference cancellation techniques are investigated.For the array-based signal processing,this paper investigates the common beamformers,including the Minimum Variance Distortionless Response(MVDR)beamformer,the zero-trap widened MVDR beamformer and the improved zero-trap widened MVDR beamformer.The advantages and disadvantages of each beamformer are evaluated by analysing the beam response and the effect of interference suppression.The effect of parameters such as the number of array elements and array element spacing on the interference suppression effect is also analysed,and the effectiveness of the interference suppression technique is verified through simulation and pool experiments.For the digital domain self-interference cancellation technique,firstly,the digital domain self-interference cancellation model based on adaptive filter algorithms(LMS algorithm,NLMS algorithm and RLS algorithm)is introduced,and the study and simulation analysis of various adaptive filtering algorithms are developed,and the performance of various algorithms is compared by the minimum mean square error(MSE)curve,and the The cancellation performance of various algorithms is compared by the minimum mean square error(MSE)curves.Subsequently,a deep neural network-based self-interference cancellation technique is proposed for the problem of convergence time in the digital domain self-interference cancellation process based on the adaptive filter algorithm,which requires a reference signal to estimate the self-interference channel response offline and complete the reconstruction of the self-interference signal,avoiding the impact of incomplete self-interference signal cancellation on the received distant expectation signal in the convergence process.The effectiveness and practicality of the proposed method are verified by simulations and pool experiments.