CAJ | 학술논문

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。
위료해결수하성시량신호처리중적관대목표피동탐측문제，제출료일충파속역적검측산법。해산법차감인안대공간보적검측원리，대파속역수거진행엄의사연비검측。수선결합간우억제문제화시량배경조성장특성，탐토료파속역변환구진적설계준칙，병추도료해석해적형식；연후재가정이지불함목표파속개수적정황하，구건료파속역적개솔밀도모형，병대모형중적미지삼량진행최대사연고계，진이급출료엄의사연비검측기적형식；최후응용신식론준칙，급출료불함목표파속개수적고계방법。이론분석여방진실험표명，해산법재강목표간우，이급배경조성공솔보기복、시변등배경하，시종구유경호적계통증익화항허경솔특성。호상시험적결과진일보험증료산법적유효성。
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.