Signal processing incorporating signal, tracking, estimation, and removal processes using a maximum a posteriori algorithm, and sequential signal detection

摘要

A system and method for automating signal tracking, estimation of signal parameters, and extraction of signals from sonar data to detect weaker signals. A maximum a posteriori (MAP) algorithm processing provides a track output of the signal which is used as a guide or template to provide optimal spectral integration on an unstable or frequency varying line. The present invention includes track integration, parameter estimation, signal track normalization, and sequential signal detection. The present invention partitions the input band into frequency subwindows. For each subwindow, the strongest signal is tracked, its parameters are estimated, and then the signal is normalized (removed) from the subwindow. This is repeated until the entire subwindow set is processed. Then the subwindows, now with their strongest signals removed, are recombined to form one input band. This aggregated procedure represents one processing pass. In the next pass, the entire above procedure is repeated with either the same or new subwindow boundaries. This continues until a predetermined number of passes is completed. Sequential signal detection is provided from one data frame to the next, a problem that is beyond the capability of conventional systems and methods for tracking frequency lines of unknown frequency modulation and amplitude.