The compressive sensor is a multispectral (MS) and hyperspectral (HS) foveal video sensor combining the cutting-edge technologies in both optical and computational fields with real-time adaptive configurability for multiple-mission applications.
Compressive sensing (CS) is a signal processing technique for efficiently acquiring and reconstructing a signal with faster and far fewer samples than required by the traditional Nyquist-Shannon sampling theory. This alternative approach is based on the principle that, by finding solutions to underdetermined linear systems and through optimization, the sparsity of a signal can be exploited to recover it via using a much smaller volume data stream.
Our CMHFVS sensor system utilizes a micro-controlled mirror array to display a time sequence of M pseudorandom basis images with a single optical sensor to compute incoherent image measurements. By adaptively selecting how many measurements to compute, the design trades off the amount of compression versus acquisition time, rather than the trade-off resolution versus the number of pixel sensors as in conventional cameras. If the single-pixel detector is replaced by a spectrometer, the sensor in the figure becomes a hyperspectral sensor.
With the unique algorithm implementation, the sensor exhibits exceptional agility enabling both multispectral (MS) sensing for wide area situational awareness and hyperspectral (HS) sensing for target recognition and identification. The sensor allows configuration of the operational parameters such as spatial, spectral and temporal resolutions based on mission requirements.
The sensor has realized the following key functions:
- Flexible switching between MS and HS sensing modes from a single sensor system;
- Fast sampling rate and imagery display refresh rate;
- Flexible fovea with arbitrary region of interest (ROI) number, size, location, and resolution in both spectral and spatial domains;
- Small foot-print profile in size, weight, and power consumption as well as cost (SWaP-C).