Iterative inverse beamforming algorithm and its application in multiple targets detection of passive

来源 :Chinese Journal of Acoustics | 被引量 : 0次 | 上传用户:chenglin229
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With the increasing of detection ability of passive sonar,the weak signal detection problem in multiple interferences becomes more and more important.In the time/bearing record(TBR) display of sonar detection,when there exist traces of multiple interferences,the identification of weak signal is difficult or impossible.The adaptive noise cancellation technique provides the theoretical basis for suppressing strong interferences.But the solution for finding the steady-state optimum filter matrix is quite difficult due to the real time calculation of inverse matrix of input data correlation matrix.The iterative inverse beamforming(IBF) algorithm for solving the optimum filter vector,which is expressed by inverse matrix of the ocean environment data,is derived in this paper,by which,the optimum filter can be eventually expressed as a sum of series simple matrices of constructed from sensor data.Based on the algorithm proposed in this paper,some examples of at sea experiment are provided.The strong interferences are cancelled and the weak signal is emerged,even it didn’t appear in the conventional beamforming(CBF) processing. With the increasing of detection ability of passive sonar, the weak signal detection problem in multiple interferences becomes more and more important.In the time / bearing record (TBR) display of sonar detection, when there are traces of multiple interferences, the identification of weak Signal is difficult or impossible. Adaptive noise cancellation technique provides the theoretical basis for suppressing strong interferences.But the solution for finding the steady-state optimum filter matrix is ​​quite difficult due to the real time calculation of inverse matrix of input data correlation matrix. The iterative inverse beamforming (IBF) algorithm for solving the optimum filter vector, which is expressed by inverse matrix of the ocean environment data, is derived in this paper, by which, the optimum filter can be expressed as a sum of series simple matrices of constructed from sensor data. Based on the algorithm proposed in this paper, some examples of at sea experiment are provided strong interferences are canceled and the weak signal is emerged, even it did not appear in the conventional beamforming (CBF) processing.
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