Partitioning algorithms in underwater passive target tracking

The area of underwater passive target tracking has received considerable attention in the past decades, due to both its theoretical interest and its practical importance in several applications. Many powerful tools from the fields of signal processing, image processing, and estimation theory have been brought to bear for the solution of the passive target tracking problem. Among the latter, techniques based on Kalman filtering and techniques based on partitioning filters have been successfully used. The approaches based on Kalman filtering do not usually perform adequately when facing a maneuvering target, whereas the techniques based on partitioning filters perform very satisfactorily in the same case. In this paper, four approaches to the problem of underwater passive target tracking, based on the partitioning theory are reviewed and discussed. Their performance is also checked against that of Kalman filtering-based approaches in both maneuvering and non-maneuvering targets scenaria