水下小孔径阵列自适应匹配滤波检测方法
doi: 10.3724/SP.J.1146.2010.01139
Adaptive Matched Filter Detection Method on Underwater Small Aperture Array
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摘要: 为了解决水下小孔径阵列有色噪声场中目标检测问题，该文提出了一种基于目标方位似然估计的自适应匹配滤波器(ML-AMF)方法，该方法采用似然方法估计目标方位，并使用预先估计的方位信息进行能量检测，通过推导得到检验统计量。该方法克服了自适应匹配滤波器(AMF)目标方位失配带来的影响。仿真和实测数据的结果均验证了该方法在水下色噪声场中的有效性。8元均匀小孔径线列阵湖试数据的仿真结果表明，ML-AMF的检测性能优于MVDR 1~5 dB，优于CBF 12~17 dB。Abstract: This paper considers detection of a signal in underwater colored noise on small aperture array, and an Adaptive Matched Filter based on Maximum Likelihood (ML-AMF) is proposed. The Direction-Of-Arrival (DOA) of signal is firstly estimated, and then energy detection is carried out by using the pre-estimated DOA. The test statistic is deduced. ML-AMF method is robust to the uncertainties of steering vector. Simulation and experiment results show the effectiveness of the method. Experiment results on an 8 element array show that ML-AMF performs better than Minimum Variance Distortionless Response (MVDR) and Conventional BeamForming (CBF) of 1~5 dB and 12~17 dB respectively.
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