Department of Electrical and Computer Engineering, University of Florida, Gainesville, Florida 32611, USA.
J Acoust Soc Am. 2013 Jul;134(1):300-11. doi: 10.1121/1.4809648.
Multistatic active sonar systems involve the transmission and reception of multiple probing sequences and can achieve significantly enhanced performance of target detection and localization through exploiting spatial diversity. This paper mainly focuses on two signal processing aspects of such systems, namely, enhanced range-Doppler imaging and improved target parameter estimation. The main contributions of this paper are (1) a hybrid dense-sparse method is proposed to generate range-Doppler images with both low sidelobe levels and high accuracy; (2) a generalized K-Means clustering (GKC) method for target association is developed to associate the range measurements from different transmitter-receiver pairs, which is actually a range fitting procedure; (3) the extended invariance principle-based weighted least-squares method is developed for accurate target position and velocity estimation. The effectiveness of the proposed multistatic active sonar signal processing techniques is verified using numerical examples.
多基地有源声纳系统涉及多个探测序列的发射和接收，并通过利用空间多样性来实现目标检测和定位性能的显著提高。本文主要关注此类系统的两个信号处理方面，即增强的距离-多普勒成像和改进的目标参数估计。本文的主要贡献是：(1) 提出了一种混合密集-稀疏方法，用于生成具有低旁瓣电平且高精度的距离-多普勒图像；(2) 开发了一种广义 K-Means 聚类 (GKC) 方法用于目标关联，以关联来自不同发射机-接收机对的距离测量值，这实际上是一个距离拟合过程；(3) 开发了基于扩展不变性原理的加权最小二乘方法，用于精确估计目标位置和速度。使用数值示例验证了所提出的多基地有源声纳信号处理技术的有效性。
