【摘要】 针对不确实海洋环境使声呐探测性能下降和宽容性差的问题,提出了环境参量和信号参量不确实性两嵌入的宽容波束形成贝叶斯方法.不确实环境参量的先验概率密度函数(probability density function,PDF)通过多项式混沌展开与传播模型相结合嵌入到接收信号的概率建模中,导出信号参量的先验PDF;接收信号参量先验PDF通过贝叶斯波束形成嵌入到处理中,转化为后验PDF.导出的后验概率最大贝叶斯波束形成具有估计器和相关器相结合的GLRT结构.仿真和实验数据分析结果表明:不确实环境参量导致接收声场发生秩扩展,由秩1扩展为秩2或秩3,贝叶斯波束形成体现了相干匹配与非相干积累的结合,实现了浅海环境中目标的正确定位,增加了宽容性.更多还原

【Abstract】 Uncertainty of oceanic environments degrades the performance and worsens the robustness of sonar.To mitigate the effect of uncertainty,a Bayesian approach to beamforming was developed which embeds the uncertainty in both environmental and signal parameters.An a priori probability density function(PDF) for uncertain environmental parameters was embedded into the probabilistic model of received signals by incorporating polynomial chaos expansions with wave propagation.This allowed the estimation,a priori PDF of signal parameters,which was in turn embedded into Bayesian beamforming to get a posteriori PDF of signal parameters.The Bayesian beamforming with maximum a posteriori probability possessed the generalized likelihood ratio test(GLRT) structure of an estimator-correlator.Examples of simulation and experiment validated the process.They showed that as the uncertainty of the environments expanded the rank of the stochastic received signal from rank 1 to rank 2 or rank 3,Bayesian beamforming combined with coherent matching and non-coherent accumulation was able to locate targets effectively in shallow water.The robustness of performance was clearly enhanced.更多还原