Imaging spectrometers are frequently used in remote sensing for their increased target discrimination capabilities over conventional imaging. Increasing the spectral resolution of these sensors further enables the system’s ability to discriminate certain targets and adds the potential for monitoring narrow-line spectral features. We describe a high spectral resolution (Δλ=1.1 nm full-width at half maximum) snapshot imaging spectrometer capable of distinguishing two narrowly separated bands in the red-visible spectrum. A theoretical model is provided to detail the first polarization grating-based spatial heterodyning of a Savart plate interferometer. Following this discussion, the experimental conditions of the narrow-line imaging spectrometer (NLIS) are provided. Finally, calibration and target identification methods are applied and quantified. Ultimately it is demonstrated that in a full spectral acquisition the NLIS sensor is capable of less than 3.5% error in reconstruction. Additionally, it is demonstrated that neural networks provide greater than 99% reduction in crosstalk when compared to pseudoinversion and expectation maximization in single target identification.
Polarization spatial heterodyne interferometry (PSHI) allows for the development of compact, vibration insensitive, high spectral resolution sensors. Introducing the imaging qualities of a lenslet array extends the advantages of PSHI to imaging interferometers. The use of Savart plates enables a birefringent interferometer that obtains higher spectral resolution with fewer optical aberrations when compared to alternative designs. In this paper, we describe the design, construction, calibration and validation of a narrowband emission line imaging spectrometer (NELIS), based on Savart plates and liquid crystal polarization gratings, along with its associated theoretical model. This sensor is advantageous for spectral imaging in the areas of remote sensing, biomedical imaging and machine vision.
Ultraspectral sensing has been investigated as a way to resolve terrestrial chemical fluorescence within solar Fraunhofer lines. Referred to as Fraunhofer Line Discriminators (FLDs), these sensors attempt to measure "band filling" of terrestrial fluorescence within these naturally dark regions of the spectrum. However, the method has challenging signal to noise ratio limitations due to the low fluorescence emission signal of the target, which is exacerbated by the high spectral resolution required by the sensor (<0.1 nm). To now, many Fraunhofer line discriminators have been scanning sensors; either pushbroom or whiskbroom, which require temporal and/or spatial scanning to acquire an image. In this paper, we attempt to quantify the snapshot throughput advantage in ultraspectral imaging for FLD. This is followed by preliminary results of our snapshot FLD sensor. The system has a spatial resolution of 280x280 pixels and a spectral resolving power of approximately 10,000 at a 658 nm operating wavelength.
High speed spectral imaging is useful for a variety of tasks spanning industrial monitoring, target detection, and chemical
identification. To better meet these needs, compact hyperspectral imaging instrumentation, capable of high spectral
resolution and real-time data acquisition and processing, are required. In this paper, we describe the first snapshot imaging
spatial heterodyne Fourier transform spectrometer based on birefringent crystals and polarization gratings. This includes
details about its architecture, as well as our preliminary proof of concept. Finally, we discuss details related to the
calibration of the sensor, including our preliminary investigations into high speed data reconstruction and calibration using
neural networks. With such an approach, it may be feasible to reconstruct and calibrate an entire interferogram cube in
one step with minimal Fast Fourier Transform (FFT) processing.