A Novel Multistatic SAR for Subsurface Imaging: Detection and Localization of Buried Pipelines and Leaks

Abstract

Ground penetrating radar (GPR) is a valuable tool widely used for many tasks in infrastructure development and maintenance, mining and archaeology, as well as in support of construction industries. As opposed to the traditional monostatic GPR system, a multistatic subsurface synthetic aperture radar (SAR) system uses a fixed transmitter to illuminate the underground and a moving receiver to sample the scattered signals around the transmitter which provides major advantages in subsurface imaging and target detection. The most notable advantages are the faster acquisition time, the improved lateral resolution, and the higher gain resulting from coherent processing. Notwithstanding, the complexity of such a subsurface SAR system introduces new challenges which this dissertation aims to address.

The first challenge is encountered in data generation using simulation. In order to evaluate the imaging performance of the subsurface SAR system, a new full-wave simulation is needed each time the receiver moves to a different position, which makes the number of simulations grow with the number of the required samples. By replacing the target with its equivalent current distribution and invoking the reciprocity theorem, this dissertation proposes a method that reduces the number of simulations required by a factor of N/2, where N is the number of samples required to form the SAR image.

Another challenge is encountered in regard to the detection and localization of buried pipelines. Since pipelines have an extended geometry, the scattering phase center on a pipeline moves as a function of the transmitter and receiver positions. This renders traditional focusing algorithms, such as the back-projection algorithm, not applicable for such a target as the scattering phase center does not appear as a fixed point with respect to the positions of the radar's transmitter and receiver. Exploiting the theoretical knowledge for pipeline scattering behavior, this dissertation develops a dynamic focusing algorithm tailored to pipelines, thereby leading to their detection and localization in multistatic SAR mode.

Building on the focusing algorithm for pipelines, which has limited range and cross-range resolutions, the dissertation provides a more general treatment for detection and localization of multiple closely-spaced pipelines. This is accomplished by developing a 3D forward scattering model for multiple pipelines, then inverting the model by minimizing the misfit between measured signals and the forward scattering model using a dynamic grid search algorithm.

The third challenge addressed in the dissertation is related to the detection and localization of buried-pipeline leaks when using the multistatic SAR mode. Due to the multiple scattering-phase-centers phenomena exhibited by pipelines, the scattered signal from the pipelines tends to overwhelm the signal scattered from the leak, making leak detection a difficult task. Utilizing the pipeline detection and localization algorithm devised earlier, the dissertation suggests a technique to identify and eliminate the pipeline contribution of the radar response, leading to better performance in leak detection.

Lastly, the problem of the direct signal leakage from the transmitter to the receiver in multistatic SAR is discussed. The leakage signal tends to be much stronger than the signals from buried targets. By incorporating array null-synthesis in the SAR processing stage, the dissertation proposes a method in which a null is created along the direction of the transmitter, thereby nulling out the leakage signal. This allows the signals from the buried objects to be detected, which ultimately leads to better imaging performance.