Sonar data conditioning by means of stepwise outlier rejection

Target signature estimation is important in passive sonar signal processing. Higher order spectral methods such as bispectral estimation are often used as a complementary tool to conventional analysis. However, these methods require larger data sets to achieve consistent estimates. The sensitivity for non-stationarities are also more pronounced for bispectral methods. Here, we use a stepwise outlier rejection algorithm as both a stationarity test and a data conditioner for experimental sonar data. We demonstrate the importance of testing for significant quadratic phase coupling and using outlier rejection as a first step in bicoherence analysis of sonar data.