Compressed sensing (CS) techniques allow for faster imaging when combined with scan architectures, which typically suffer from speed. This technique when implemented with a subterahertz (sub-THz) single detector scan imaging system provides images whose resolution is only limited by the pixel size of the pattern used to scan the image plane. To overcome this limitation, the image of the target can be oversampled; however, this results in slower imaging rates especially if this is done in two-dimensional across the image plane. We show that by implementing a one-dimensional (1-D) scan of the image plane, a modified approach to CS theory applied with an appropriate reconstruction algorithm allows for successful reconstruction of the reflected oversampled image of a target placed in standoff configuration from the source. The experiments are done in reflection mode configuration where the operating frequency is 93 GHz and the corresponding wavelength is λ = 3.2 mm. To reconstruct the image with fewer samples, CS theory is applied using masks where the pixel size is 5 mm × 5 mm, and each mask covers an image area of 5 cm × 5 cm, meaning that the basic image is resolved as 10 × 10 pixels. To enhance the resolution, the information between two consecutive pixels is used, and oversampling along 1-D coupled with a modification of the masks in CS theory allowed for oversampled images to be reconstructed rapidly in 20 × 20 and 40 × 40 pixel formats. These are then compared using two different reconstruction algorithms, TVAL3 and ℓ1-MAGIC. The performance of these methods is compared for both simulated signals and real signals. It is found that the modified CS theory approach coupled with the TVAL3 reconstruction process, even when scanning along only 1-D, allows for rapid precise reconstruction of the oversampled target.
Millimeter (mm) and sub-mm wave radiation is increasingly becoming a region of interest as better methods are developed to detect in this wavelength range. The development of sensitive focal plane array (FPA) architectures as well as single pixel scanners has opened up a new field of passive detection and imaging. Spectral signatures of objects, a long standing area of interest in the Short Wave Infrared (SWIR), Mid-Wave (MWIR) and Long Wave-IR (LWIR) bands can now be assessed in the mm-wave/terahertz (THz) region. The advantage is that this form of radiation is not as adversely affected by poor atmospheric conditions compared to other bands. In this study, a preliminary experiment in a laboratory environment is performed to assess the radiance from targets with low infrared signatures in the millimeter wave/terahertz (THz) band (<1 THz). The goal of this approach is to be able to model the experimental results to better understand the mm-wave/THz signature of targets with low observability in the IR bands.
The development of passive and active millimeter wave imaging systems is progressing rapidly fueled by the need for many applications in the area of security and defense. Imaging schemes that may either utilize array detectors or single detectors in scan architectures offer suffer from poor resolution due to the longer wavelengths used and the limits of the optical system in terms of lens and mirror dimensions. In order to overcome this limit, super-resolution techniques can be employed to enhance the resolution of the imaging system. Here, a form of this technique based on oversampling is applied to reconstruct the image of a target which is acquired using compressive sensing based on scanning the image plane using randomly patterned masks with fixed pixel sizes. The mm-wave stand-off imaging system uses a 93 GHz center frequency source and heterodyne sub-harmonic receiver place in a bi-static configuration to image a target in reflection mode. The image of the target is projected onto a mechanically scanned spatial light modulator (SLM), which is a patterned two-dimensional mask that is translated along one axis. In order to improve the resolution of the image, the masks are shifted by half the pixel size (2.5mm). To enhance the resolution of the image, the patterns are shifted by smaller steps, thereby each pixel is oversampled and the resulting new pattern and detected intensity is fed into the CS algorithm to reconstruct the image of the target. After the image reconstruction process, sharper edges are observed for a circular object of 12mm diameter compared to the image acquired by whole pixel step scanning.