Matched mode space detector in shallow-water environments

Incorporating the law of underwater sound propagation into algorithm design can improve passive sonar detection performance. When the source position is unknown, the Generalized Likelihood Ratio (GLR) and Bayesian detectors handle this uncertainty via searching and integration. However, both detectors suffer from great performance degradation in some source-position cases when they are implemented by only a finite number of signal wavefronts. Exploiting the physics of underwater sound propagation this paper proposes a robust subspace detector the Matched Mode Space Detector (MMSD), robust in the sense that it can provide a consistent performance in different sourceposition cases given the radiated sound signal energy impinging on the array. The MMSD utilizes the environmental knowledge from the mode space and thus can obtain a better robust performance than the ED, which also has the stone performance robustness. The simulation results in a typical shallow-water channel suggest that compared with the traditional GLR and Bayesian detectors, the MMSD is just slightly inferior in terms of the performance peak, requires much fewer computational loads and enjoys a better tolerance to environmental mismatch.