用极点方法识别水下目标

本文中研究一种水下目标识别方法并介绍一组材料、大小、厚度不同的中空圆柱形水下目标的识别实验。我们分三步提取水下目标特征量。第一步是在频域上用短脉冲作为入射信号辨识脉冲响应函数。第二步用“卷积-修正递推最小二乘”法估计目标ARMA模型参数。第三步计算频域上的极点。我们用极点作为水下目标的特征量,并认为它是一个不变量。计算机模拟结果表明,同以AR参数作为特征量的方法相比较,极点法的抗噪声干扰能力改善12dB。我们采用匹配滤波分类器对水下目标进行分类。实验结果表明,在无噪声情况下,正确识别率可达100％。信噪比 关键词：

RECOGNIZING UNDERWATER TARGETS BY THE METHOD OF THE POLES

This paper examines the recognition of underwater targets by the method of the poles and presents the experimental results. The underwater targets used in experiment are hollow cylinders made from different materials, and with different lengths and thicknesses.The features of the underwater target are extracted in the following three steps. First, the impulse response function of the target is identified in the frequency domain by using the short pulse as the incident signal. Second, the method of the so-called "convolution-modified recursive least-squares" is employed to estimate the parameters of the ARMA model of the target. Third, the poles are calculated in the frequency domain. The poles are adopted as the features of the target and considered to be a constant quantity. The computer simulation shows that the anti-noise ability of the method of the pole is 12dB improved compared with the AR model.In the experiment, the matched- filtering classifier is applied to classify the underwater target. The experimental results has demonstrated that 100% correct recognition rate can be achieved for signal-only cases. With white noise added to the echoes, 100% correct recognition rate is still achieved when signal-to-noise ratio is as low as 8dB, and 87.5% correct recognition rate is achieved for S/N = 5dB.