The impacts of scene stability and acoustic backscatter coherence on automated seabed change detection

Abstract

Practical implementation of long-term seabed monitoring for civilian and military activities requires automated tools for detecting temporal seabed changes, such as for detection of new trawling activities or mine-like objects on the seafloor. Automated Change Detection (ACD) identifies relevant changes in a particular area of seabed by comparing a pair of Synthetic Aperture Sonar (SAS) images collected before and after the change. Some amount of time after the baseline SAS image data is collected, the same seafloor scene is resurveyed, producing the repeat-pass image. Predicting the optimal time interval between images, known as the resurvey frequency, is needed for the best implementation of ACD. Presently, there is no standard procedure for determining the resurvey frequency that optimizes ACD performance. This paper discusses recent work on factors affecting seabed stability and impacts on requirements for resurvey frequency and effectiveness of ACD. The ACD processing chain can be summarized in four steps: (1) collect a pair of baseline and repeatpass images, (2) co-register/align the images, (3) generate a change map1,2, and (4) detect changes of interest, along with false alarms. There are multiple techniques for co-registering image pairs; for example, one method applies a large-scale alignment followed by a small-scale co-registration3,4. ACD methods applied to multi-temporal SAS imagery can be broadly categorized as incoherent (ICD) or coherent (CCD). ICD techniques process the mean backscatter power of the images, while CCD employs both the amplitude and phase of the backscattered energy. Generally, CCD demonstrates increased sensitivity to small changes, while ICD is more robust over longer time intervals5,6. This is because utilizing the phase difference between two complex images (i.e. interferogram) can lead to the detection of a physical disturbance in the scene even when there is negligible change in amplitude, such as a slight disturbance of the seafloor or the introduction of an object that has similar scattering properties to the seabed. Figure 1 shows multi-temporal SAS seafloor imagery with a physical change (likely an animal track traversing one burrow to another) that is apparent only in phase, resulting in it being detectable in the coherent change map3.