Research On Central Moment Beamforming

The high-precision underwater target detection has been one of the important issues in underwater acoustic signal processing. However, due to the complexity of the ocean environment, many high-resolution algorithms in practical engineering applications work badly. Therefore there is an urgent need for a high reliability and high-resolution algorithm. Around the subject, this paper discusses a new beamforming algorithm:the Central Moment Beamforming (CMBF).Since most of the high-resolution algorithm is based on subspace decomposition theory, the numbers of signal sources are needed for data covariance matrix decomposition, if the numbers are not exactly, there will have a great impact, even misjudgment, on the performance of the algorithm. In addition, most of the high-resolution algorithm is sensitive to array errors and perform poorly in low signal-to-noise ratio environment. They are the shortcomings to the application of high-resolution algorithm in practical engineering. Essentially, CBF algorithm is based on statistical characteristics:mean (first order origin moment), its robustness in engineering applications has been proved. Is there be an algorithm which is based on the statistical characteristics and has a robust high-resolution algorithm? In this point, this paper shows the central moments beamforming algorithm. This method is based on the statistical characteristics:the central moment, has high resolution and high robustness which meet the needs of high-precision underwater target detection.Firstly shows the concept of moment beamforming, and point out the CBF algorithm equates first order origin moment beamforming. Discuss the defects of the high order origin moment algorithm by their mathematical expressions. Then the paper discusses the principle and mathematical expressions of the CMBF algorithm in detail, and. pointed out the advantages of CMBF algorithm performance compared to other algorithms by the theory and simulation analysis. At the same time to shortcoming of complicated calculations of CMBF, invent a simple algorithm of second order CMBF based on the data covariance matrix. Finally, the data of lake experiment processing results show that:compared to other beamforming algorithms, CMBF algorithm has better resolution and lower sidelobe level, is consistent with the conclusions of the theoretical analysis. There is the conclusion that the Central Moments Beamforming algorithm is a robust high-resolution algorithm, it can satisfy the needs of high-precision underwater target detection.