ML estimation of seafloor topography using multi-frequency synthetic aperture sonar

In this paper we investigate synthetic aperture sonar (SAS) broadband interferometric height estimation using multiple frequency bands. The height estimate is generated using a maximum likelihood (ML) estimate combining the data from the hydrophones. To decrease the effect of the large variance of the phase difference estimates the broadband signal is divided into smaller subbands and combined to give a height estimate with much improved accuracy, albeit at a reduced resolution due to the reduction in system bandwidth. Results are shown for a two element sonar, and the improvement obtained using multiple frequency bands subbanded to give a lower variance in the height estimate. Multiple pings are also combined as multiple looks, further reducing the height variance.