Concurrent detection and localization of buried targets using track-before-detect processing

Abstract

The GOATS (Generic Oceanographic Array Technology Systems) Joint Research Program explores the development of environmentally adaptive autonomous underwater vehicle (AUV) technology for Rapid Environment Assessment and Mine Counter Measurement (MCM) in coastal environments. MIT is developing the GOATS multistatic sonar concept which uses a low-frequency source on one AUV to subcritically insonify the seabed over a wide area, while a formation of multiple AUVs are used for mapping the associated 3-D scattered acoustic field in the water column. Exploring the different characteristics of the scattering from various buried targets, an algorithm has been developed for autonomous, concurrent detection and localization of buried targets. At the subcritical isonification angles necessary to sustain high coverage rate, the buried target detection depends on the measurement of very weak signals, in general undetectable by traditional detect-before-track algorithms. The method developed here applies a Track-Before-Detect (TBD) approach to solve this problem. This technique tracks the AUV trajectory first using the slowly changing environment information, and then the weak signal detection is declared after the AUV track is estimated at sufficient level of confidence. This new algorithm has been applied on the GOATS-2000 bistatic data. The result shows the successful navigation results by confident detection of three buried targets, two of which are particularly weak scatterers. A real-time, autonomous implementation of the algorithm was recently demonstrated in the GOATS-2002 experiment, and the result for both experiments will be discussed. [Work supported by ONR.]