High resolution, low-frequency, ultra-wideband radar system

Utilizes noise extraction algorithms for enhanced imaging


Conceptual illustration of airborne video synthetic aperture radar by DARPA.

A critical challenge for low-frequency UWB radar is that collected radar information is susceptible to corruption by radio frequency interference within the huge operating spectrum. The radar signal spectrum in this case contains significant overlaps with those of radio, TV, cellular phone, wireless networking, amateur radio, etc., resulting in a poor signal-to-noise ratio and ultimately reducing the effectiveness of target detection and classification.

Mitigation of radio interference is a notoriously challenging problem due to the dynamic and unpredictable nature of the noise sources, not to mention the strength of the noisy signals. Still, UWB has tremendous value in detection of obscured objects e.g., in foliage, buried in the ground, and moving behind walls or barriers and has utility spanning major industries including healthcare and energy.

Recently, Army researchers developed a low-frequency UWB radar system which delivers excellent penetration capability while maintaining high image resolution.  The radar transmits in pulse repetition intervals to illuminate the area of interest and receives return radar signals that correspond to the physical objects from the area. The return radar signals are severely contaminated by many interference sources.

The key to this system is the joint, sparse, and low-rank signal recovery processor which employs a dictionary of impulses, i.e., an identity matrix. The signal recovery processor estimates, separates, and extracts the noise signal components via a separation process where the RFI is modeled as low-rank components while the meaningful synthetic aperture radar (SAR) signals are treated as sparse outliers embedded on top.

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