基于最小二乘的短垂线阵匹配场处理

Matched Field Processing Based on the Least Squares Algorithm for Short Vertical Linear Array

匹配场处理通常要求接收基阵能够覆盖整个水层,如此大尺度的布阵方式严重阻碍了该方法的广泛使用。为了缓解匹配场处理对阵形的苛刻要求,该文提出一种基于最小二乘的短垂线阵匹配场处理技术。该方法把接收阵的声场分解为模态函数矩阵和模态系数向量,并在最小范数意义下用最小二乘算法得到了各阶模态系数的估计值,在此基础上重新构造了短垂线阵的测量场向量,使得重构后的测量场包含更多的环境信息,从而提高了短垂线阵匹配场处理的性能。最后,在典型的Pekeris波导环境中进行仿真,以3种布放在水面附近的短垂线阵为例,分析了匹配场被动定位的性能,并用广义余弦量化分析了不同布阵方式对测量场的影响。结果表明:使用最小二乘算法对短阵的测量场进行声场重构后广义余弦变大,此时短垂线阵匹配场处理的定位性能得到改善,验证了该算法的有效性。

The receiver array of matched field processing usually needs to cover the whole water column, such a large arrangement of array hinders its application seriously. To overcome this shortcoming, an approach called matched field processing based on least squares algorithm is proposed, which decomposes the received fields into depth function matrixes and amplitudes of normal mode at the beginning. Then all the mode amplitudes are estimated using the least squares in the sense of minimum norm. Next, the amplitudes estimated are used to reconstruct the received fields of the short vertical linear array, which makes the reconstructed ones contain more environmental information, therefore the performance of matched field processing with short array is improved. In the end, lots of simulations with three short vertical arrays which are located near by water surface are processed in the classical Pekeris waveguide, and the performance of matched field passive localization is evaluated. Meanwhile, in order to quantify the influence of different kinds of geometrical arrangements to the received fields, the generalized cosine-squared between two vectors is used. The results show that when the received fields of short array are reconstructed using the least squares, the generalized cosine-squared is larger obviously, finally the performance of matched field passive localization with short array is improved and the proposed algorithm is proved to be effective.