UC Merced

When target sizes are comparable to the inherent resolution of a synthetic aperture radar (SAR) imaging system, images only produce representative points which can be used to detect and locate different targets, but not distinguish any further between them. Using those representative points reconstructed with traditional SAR imaging, we introduce a method that recovers a frequency spectrum from the same set of measurements. We show theoretically that this spectrum is related to the radar cross‐section of the target. For special cases when the proposed method is not able to distinctly image or recover frequency spectra from two different targets, we introduce modifications that resolve those issues. Using numerical simulations, we show that this spectrum provides valuable information allowing for differentiating targets that would otherwise be indistinguishable. Moreover, this method does not require any additional data than that already used for imaging. Including this spectral characterization opens opportunities to consider alternate strategies for managing resources for collecting and recovering target features contained in SAR measurements. Any synthetic aperture radar imaging system has spatial resolution limits based on various system parameters such as bandwidth, synthetic aperture size, elevation height, etc. As a result, when two or more targets in an imaging region are comparable or smaller than those resolution limits, reconstructed images cannot distinguish between them. At best, we find that typical synthetic aperture radar (SAR) images only produce representative points for those targets. However, characterizing targets beyond these representative points may be important for various applications. For example, it may be useful for ruling out false positives. To characterize targets beyond what these typical images can do, we describe a method that recovers a spectral signature for each target using the same SAR measurements used for imaging. This signature is directly related to the target's radar cross‐section as a function of frequency over the system bandwidth. We propose recovering this spectrum to enable the classification of targets which otherwise would be indistinguishable. In this work, we discuss the theoretical background for this method, consider special cases requiring modifications to the method, and validate our theory using numerical simulations. Targets whose sizes are comparable to the resolution of a synthetic aperture radar (SAR) imaging system are indistinguishable The frequency content of SAR measurements contains characterizing spectral information about those targets We analyze a method that identifies and locates targets and then uses those results to recover spectra that characterize them Targets whose sizes are comparable to the resolution of a synthetic aperture radar (SAR) imaging system are indistinguishable The frequency content of SAR measurements contains characterizing spectral information about those targets We analyze a method that identifies and locates targets and then uses those results to recover spectra that characterize them