Estimation and detection issues in matched-field processing

A conceptual framework in which the model-based, space-time acoustic signal processing procedure known as matched field processing (MFP) can be handled in a consistent manner is established. A framework for strong-signal MFP based on standard statistical estimation theory, in which MFP is regarded as essentially an estimation problem in the strong-signal regime, is developed. In the weak-signal case, the necessary requirement of detection dictates that MFP then be considered a joint detection-estimation task. It is demonstrated that, generally, MFP is essentially a space-time processing problem rather than simply an array processing (spatial processing only) procedure. An overview of the processing schemes used to date in MFP is given, showing how these methods relate to the optimal space-time structure. Weak-signal detection and estimation scenarios relevant to MFP are then noted. Present methods for dealing with the inherent instability of MFP algorithms (mismatch) are discussed. The current status of MFP is summarized, and recommendations for future research are made