常规的检测算法在实际不确定海洋环境中会遇到环境失配的问题,进而导致检测性能下降。本文结合贝叶斯原理和广义似然比方法,基于蒙特卡罗优化技术,提出了一种不确定海洋环境中信号检测方法。该检测器将环境先验信息应用到广义似然比检验中,在保证有效检测的基础上,降低了计算复杂度。同时给出了精确模型匹配检测器、最优贝叶斯信号检测器、平均模型匹配检测器和能量检测器作为对比的检测算法。计算机仿真和SWellEx-96海上实测数据处理结果表明,本文提出的信号检测器检测取得了优于平均模型匹配检测器和能量检测器的性能,其计算效率也有明显提高。 Conventional detection algorithms may encounter environmental mismatch problems in the actual uncertain marine environment, leading to a decrease in detection performance. In this paper, Bayesian principle and generalized likelihood ratio method, based on Monte Carlo optimization techniques, presents a signal detection method in uncertain ocean environment. The detector applies the prior information of the environment to the generalized likelihood ratio test, which reduces the computational complexity on the basis of ensuring effective detection. At the same time, the exact model matching detector, the optimal Bayesian signal detector, the average model matching detector and the energy detector are given as contrast detection algorithms. Computer simulation and SWellEx-96 sea data measurement results show that the signal detector proposed in this paper has achieved better performance than the average model matching detector and energy detector, and its computational efficiency has also been significantly improved.