Research On Passive Detection Technology Of Underwater Target Using Acoustic Vector Sensor Array

In order to improve the detection performance of remote target in passive sonar system under the background of strong interference and complex underwater acoustic environment,a theoretical and experimental researches on the methods of remote target detection using acoustic vector sensor array(AVSA)was carried out according to the latest trends of acoustic vector signal process,as well as the technique of beamforming,spatial spectrum estimation,and line spctrum signal process.Aiming at the problem of MVDR beamformer based on AVSA seriously suffers from performance degradation in the presence of array model mismatch errors,a novel robust adaptive beamforming algorithm was proposed.Combined with adaptive canceling using vector sensor,the desired signal was suppressed in each acoustic pressure and particle velocity channel of AVSA,then the classic diagonal loading algorithm was realized with the new covariance matrix gained by this preprocess.Both theoretical analysis and computer simulations show that,compared with the traditional diagonal loading robust method,the proposed algorithm can keep better strong target interference suppress ability in the premise of improving the robustness of adaptive beamformer,and also can avoid the performance degradation due to the improper parameter setting.Aiming at the problem of robust adaptive beamforming under the background of fast moving targets,a novel beamforming algorithm with automatically broadening null was proposed.By studying on the variation law of direction of arrival(DOA)of uniform line motion target,the DOA prediction method based on history direction information was given,the null with proper width can be generated by using this forecasting information.Both theoretical analysis and computer simulations show that,compared with Mailloux method and Zatman method,the proposed algorithm can achieve higher spatial gain against the isotropic noise when suppressing the fast moving target interference,the better output SINR performance is exhibited under the condition of single or multiple moving target interference.Aiming at the problem of detecting acoustic broadband signal with continuous spectrum,a novel detection algorithm based on beam space transformation is proposed.The principal of spatial spectrum detection with human eyes is employed for reference,and the generalized likelihood ratio test(GLRT)is applied on beam space.Firstly,the design criterion of beam space transformation matrix is studied for a comprehensive consideration of the environment of multiple targets interference and the characteristic of vector ambient noise field,and the analytical solution is obtained.Secondly,assuming that the number of beams not containing target signal is known,the probability density function(PDF)model of beam space data is constructed,and the new GLR test is derived by calculating the maximum likelihood estimates of the unknown variables in PDF.Finally,the information theoretical criterion is adopted in order to estimate the number of beams not containing target signal.The processing gain and the threshold value of this test statistics are also discussed,and the specific implement is explained in detail.Theoretic analysis and simulation results show that under the complex condition of strong target interference as well as ambient noise with undulate and time-variant power spectrum,the proposed algorithm can give the processing result with higher gain and the detection threshold with constant false alarm rate(CFAR),the lake experiment results further prove the favorable and robust detection performance.Aiming at the problem of detecting acoustic target with periodical modulation characteristics,a novel fuzzy detection algorithm on broadband modulation signal using AVSA is proposed.Firstly,the blind area of passive detection under the background of strong target interference is researched,and it is pointed out that the detection ability of weak target in blind area can be enhanced by using the periodical modulation feature of propeller noise.Secondly,the FIR broadband adaptive beamforming technology is applied to the output data of acoustic vector sensor array in different frequency band,and the fuzzy test statistic of shaft frequency is obtained by means of fuzzy algorithm,which is able to improve the detection performance of the traditional maximum likelihood(ML)test statistic under the imperfect condition in practical engineering application.Finally,the transient parameter sequence is obtained by threshold decision and spectrum peak search,and the fuzzy system is constructed again to extract every periodical modulation target's bearing time track through analyzing on this sequence.Theoretic analysis and simulation results show that under the imperfect condition of the harmonic frequency excursion caused by the asymmetric propeller as well as the ambient noise with undulate power spectrum,the proposed algorithm can always give a better performance.The lake experiment results prove that the weak target can be detected effectively even in the blind area of sonar system.