Approximately optimal distribution of depth sensors over towed array

作者：Wen Shulin; Li Shuqiu^*; Hao Chengpeng

来源：IET Signal Processing, 2018, 12(6): 770-776.

DOI：10.1049/iet-spr.2017.0547

• sensor arrays
• shape measurement
• least mean squares methods
• depth sensor
• approximately optimal distribution
• towed array shape estimation method
• nonacoustic sensor
• computational complexity
• Kalman filter
• minimum space average mean square error
• AMSE

Towed array shape estimation aided with non-acoustic sensors is widely used for its rather low computational complexity of solutions and rather explicit results. In addition, previous studies have emphasised that depth sensors' distribution has a dramatic influence on the accuracy of this kind of array shape estimation method. Established on the basic theory of towed array shape estimation using Kalman Filters, the approximately optimal distribution of a certain number of depth sensors over a certain number of discretised towed arrays yields the approximately best achievable performance in terms of minimum space average mean square error (AMSE), is addressed in this study. The effect of depth sensors' distribution has been discussed. Then an exact expression for the space AMSE is derived. The expression is simplified in a reasonable way considering the practical issues in order to calculate the minimum space AMSE rapidly and effectively. The performance assessments demonstrate the effectiveness of the newly proposed method.

• 出版日期2018-8
• 单位中国科学院大学; 中国科学院声学研究所