Research On Interference Suppression Technology Under Strong Interference

With the development of vibration and noise reduction technology,the radiation noise of underwater vehicle is obviously reduced.In the Marine environment noise,the detection of underwater vehicles is often affected by far field strong interference such as surface ships or fishing boats,so that the target radiation noise is often submerged by strong interference.Therefore,how to suppress strong interference signals and realize the detection of weak target signals has become an urgent research problem to be solved.This paper mainly studies the strong interference suppression algorithm based on null constraint beamforming and robust null constraint beamforming,and combines the fourth-order cumulant to improve the performance of weak target estimation.This paper first studies the classical beamforming algorithm,on this basis,by setting the null constraint condition in a specific direction,studies the null constraint beamforming algorithm,which can suppress the strong interference signal,and verifies the strong interference suppression performance of the null constraint beamforming algorithm through simulation.However,the null constraint beamforming algorithm is not robust when there are errors in the array covariance matrix,expectation and interference guidance vector in the real Marine environment.Aiming at the errors existing in the real Marine environment,a robust beamforming algorithm is studied.Bartlett null constraint algorithm with null trap broadening can be used to solve the problem that null trap can be generated in the direction of interference due to the mismatching of the guiding vector of interference signals.For linear constrained minimum variance beamformers,the diagonal loading method is used to solve the problem of the performance loss caused by the covariance matrix of small snapshot data.The eigenspace method is used to solve the performance loss caused by the mismatching of expected signal guidance vector.Combined with the advantages of the first two robust algorithms,the joint robust algorithm based on eigenspace projection solves the problem of algorithm performance loss caused by the error of covariance matrix and the error of estimating the expected signal guidance vector,and can realize that the output signal-to-noise ratio is still good in small fast shooting,and the output signal-to-noise ratio is not affected by the Angle difference when the signal angle error are within ±1.4°.Simulation and sea test data verify that the proposed robust algorithm has the performance of strong interference suppression and direction finding for weak targets.Aiming at the gauss characteristics of Marine environmental noise,a robust interference suppression algorithm based on the fourth order cumulant is proposed in combination with the advantage that the fourth order cumulant algorithm can completely eliminate Gaussian noise theoretically.The robust interference suppression algorithm based on the fourth order cumulant is compared with the simulation and sea test data.It is verified that the robust interference suppression algorithm based on the fourth order cumulant not only retains the performance advantage of the robust interference suppression algorithm to improve the performance of the interference suppression algorithm when errors exist,but also reduces the background noise,and has better performance of strong interference suppression and weak target estimation.