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中文摘要：
为了解决水下声矢量信号处理中的宽带目标被动探测问题，提出了一种波束域的检测算法．该算法借鉴人眼对空间谱的检测原理，对波束域数据进行广义似然比检测．首先结合干扰抑制问题和矢量环境噪声场特性，探讨了波束域变换矩阵的设计准则，并推导了解析解的形式；然后在假定已知不含目标波束个数的情况下，构建了波束域的概率密度模型，并对模型中的未知参量进行最大似然估计，进而给出了广义似然比检测器的形式；最后应用信息论准则，给出了不含目标波束个数的估计方法．理论分析与仿真实验表明，该算法在强目标干扰，以及背景噪声功率谱起伏、时变等环境下，始终具有更好的系统增益和恒虚警率特性．湖上试验的结果进一步验证了算法的有效性．
英文摘要：
Aiming at the problem of passive detection of broadband sources in underwater acoustic vector signal processing, a novel detection algorithm based on beam-space transformation is proposed. The principle of spatial spectrum detection with human eyes is employed for reference, and the generalized likelihood ratio test （GLRT） is applied to the beam-space. First, the design criterion of beam-space transformation matrix is studied for the comprehensive consideration of the environment of multiple targets and the characteristic of vector ambient noise field, so that the analytical solution is obtained. Second, assuming that the number of beams not containing the target signal is given, the probability density function （PDF） model of beam-space data is constructed, and the new GLR test is made by calculating the maximum likelihood estimate of the unknown variables in PDF. Finally, the information of theoretical criterion is adopted in order to estimate the number of beams not containing target signals. The processing gain and the threshold value of this test statistics are also discussed, and the specific implement is explained in detail. Theoretical analysis and simulation results show that under the complex conditions of strong target interference and ambient noise with undulated and time- variant power spectrum, the proposed algorithm can give the processing result with higher gain and detection threshold at constant false alarm rate （CFAR）; the results of lake experiment further prove the favorable and robust detection performance.
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