Patent Description:
The subject matter disclosed herein relates generally to spectrometry and more specifically to reconstructive spectrometry.

A spectrometer may be used to measure the properties of light over one or more portions of the electromagnetic frequency spectrum including, for example, ionizing radiation (e.g., gamma radiation, hard x-rays, soft x-rays), optical waves (e.g., near ultraviolet, near infrared, mid infrared, far infrared), and/or microwaves and radio waves. Conventional grating-based spectrometers typically rely on dispersive optics (e.g., a prism and/or a grating) to separate incoming light into a spectrum of the light's component wavelengths. The diffracted light may subsequently be propagated (e.g., by one or more reflective mirrors) onto a sensor (e.g., photodiodes and/or photo transistors) configured to measure the optical power or intensity (e.g., energy per unit of area) of each of the component wavelengths. <CIT> describes a method of optical spectroscopy and a device for use in optical spectroscopy. The device includes a substrate, and a plurality of etalon cavities affixed to or coupled to the substrate. A signal is received from a Fabry-Perot interferometer. The signal is sampled using the device according to a generalized Nyquist-Shannon sampling criterion. The signal is sampled using the device according to a phase differential criterion for wave number resolution. An input spectrum for the signal is reconstructed based on the signal sampled according to the generalized Nyquist-Shannon sampling criterion and the signal sampled according to the phase differential criterion for wave number resolution. <NPL> describes that traditional Fabry-Perot (FP) spectroscopy is bandwidth limited to avoid mixing signals from different transmission orders of the interferometer. Unlike Fourier transformation, the extraction of spectra from multiple-order interferograms resulting from multiplexed optical signals is in general problematic. Using a Fourier transform approach, a generalized Nyquist limit appropriate to signal recovery from FP interferograms is derived. <CIT> describes an optical detector device for generating at least one electrical output signal in response to a received beam of light, comprising an optical band-pass filter, adapted to receive the beam of light and to provide a filtered beam of light. <CIT> describes a method comprising: providing a first layer of material; selectively treating portions of the first layer such that differently treated portions exhibit different degrees of material volatization from the first layer to form different levels. <CIT> describes a spectrometer for use with a desired wavelength range which includes an array of filters. Each filter outputs at least two non-contiguous wavelength peaks within the desired wavelength range. The array of filters is spectrally diverse over the desired wavelength range, and each filter in the array of filters outputs a spectrum of a first resolution. An array of detectors has a detector for receiving an output of a corresponding filter. A processor receives signals from each detector, and outputs a reconstructed spectrum having a second resolution, the second resolution being higher than any of the first resolution of each filter. <CIT> describes reconfigurable MEMS fabry-perot tunable matrix filter systems and methods, wherein an optical apparatus includes a plurality of Fabry-Perot cavities and a controller. <CIT> describes a spectral characteristics acquisition apparatus, an image evaluation apparatus and an image forming apparatus for simultaneously acquiring the brightness information on an image by the same sensor. <CIT> describes a color filter substrate which includes a transparent substrate, a first and second reflective layers, a spacer layer, and an interference layer.

The claimed invention is defined by the independent claims <NUM> and <NUM>, while preferred embodiments form the subject of the dependent claims. Systems and methods are provided for filter array spectrometry.

While certain features of the currently disclosed subject matter are described for illustrative purposes in relation to an enterprise resource software system or other business software solution or architecture, it should be readily understood that such features are not intended to be limiting. The claims that follow this disclosure are intended to define the scope of the protected subject matter.

The accompanying drawings, which are incorporated in and constitute a part of this specification, show certain aspects of the subject matter disclosed herein and, together with the description, help explain some of the principles associated with the subject matter disclosed herein. In the drawings,.

Conventional spectrometers may measure the properties of light (e.g., intensity) by at least diffracting incoming light (e.g., into a spectrum of the light's component wavelengths) and propagating the diffracted light onto a sensor (e.g., an array of photodiodes and/or photo transistors). However, performing these operations typically requires a large number of moving optical components (e.g., prisms, gratings, and/or reflective mirrors), which renders conventional spectrometers excessively bulky, fragile, and expensive. Thus, despite its many useful applications, spectrometry has thus far failed to proliferate beyond the laboratory.

In some example embodiments, a filter array spectrometer may include a filter array with a plurality of filters acting as optical resonators. Each filter in the filter array may be an etalon that is configured with a specific passband. Thus, as light passes through the filters in the filter array, each filter may attenuate at least one wavelength (or portion of the spectrum) that is outside of the passband of the filter while allowing the transmission of at least one other wavelength (or portion of the spectrum) that is in the passband of the filter. The output of each filter in the filter array may be an output spectrum that forms a transmission pattern. This transmission pattern may include multiple transmission peaks corresponding to the wavelengths (or portions of the spectrum) that is able to pass through the filter. According to some example embodiments, the filter array may include filters that are different in thickness because different thickness filters may generate different transmission patterns that are unique to each filter. The resulting plurality of unique transmission patterns (e.g., generated by different filters in the filter array) may be used to reconstruct the full spectrum of the light passing through the filter array.

In some example embodiments, a plurality of transmission patterns from different thickness filters (e.g., etalons) in a filter array may be used to reconstruct the original spectrum of light passing through the filter array. Each transmission pattern may include a sampling of the wavelengths in the original spectrum of light. Thus, the original spectrum of the light may be recovered by at least applying one or more signal reconstruction techniques (e.g., compressed sensing and/or the like) to at least determine an approximation of the original spectrum that best fits the transmission patterns generated by all the filters in the filter array. It should be appreciated that a filter array configured in accordance to various embodiments of the present disclosure may be both compact and inexpensive. Moreover, a filter array spectrometer formed from such a filter array may contain no moving parts and may therefore be more robust than conventional spectrometers (e.g., grating-based spectrometers). Thus, in some example embodiments, a filter array spectrometer may be deployed for a gamut of applications including, for example, lab-on-chip measurements, field spectrometry, space instrumentation, and embedded systems.

In some example embodiments, the spectrum of the light that is emitted, reflected, and/or transmitted by an object may be used to analyze the object. For instance, an object may emit, reflect, and/or transmit light (e.g., in the mid-infrared range) that may be specific to the molecules present in the object. Thus, the spectrum of light emitted, reflected and/or transmitted by the object may serve as a spectral signature that may be used to determine the molecular composition of the material and/or compound forming the object. Alternately and/or additionally, the object may emit, reflect, and/or transmit thermal electromagnetic radiation (e.g., black-body radiation in the mid-infrared range) that may be used for passive thermal vision and/or temperature measurements. For clarity and conciseness, various embodiments of the present disclosure are described with respect to light waves. However, the subject matter disclosed herein may also be applied to other wave-like phenome including, for example, acoustic waves, seismic waves, gravity waves, and/or mechanical waves. Furthermore, it should be appreciated that a light source may be used to actively illuminate the object, when there is insufficient light in the surrounding environment to cause light to be emitted, reflected, and/or transmitted from the object. However, the filter array spectrometer may also be able to capture light that is passively emitted, reflected, and/or transmitted by an object without an active external light source.

In some example embodiments, a filter array spectrometer may have a compact form factor that enables the filter array spectrometer to be integrated into a portable device including, for example, a smartphone, a tablet personal computer (PC), a laptop, a robot, a drone, a wearable device, and/or the like. For example, the filter array spectrometer may be integrated into a smartphone camera by at least including, in the camera, the filter array while the smartphone's processor may be utilized for spectrum reconstruction. Thus, according to some example embodiments, the form factor of the filter array spectrometer may render the field array spectrometer especially suitable for field spectrometry. For instance, the filter array spectrometer may be used to determine, based on light emitted, reflected, and/or transmitted from various objects, the molecular composition of these objects. As one illustrative example, a smartphone camera with an integrated filter array may be used to capture the light emitted, reflected, and/or transmitted by a food item in order to determine the fat and/or sugar content of the food item.

<FIG> depicts a block diagram illustrating a reconstructive spectrometry system <NUM>, in accordance with some example embodiments. Referring to <FIG>, the reconstructive spectrometry system <NUM> may include a filter array spectrometer <NUM> and a spectrum generator <NUM>. As shown in <FIG>, the filter array spectrometer <NUM> and the spectrum generator <NUM> may be communicatively coupled via a wired and/or wireless network <NUM>, which may be a local area network (LAN), a wide area network (WAN), and/or the Internet. Here, the filter array spectrometer <NUM> may operate remotely from the spectrum generator <NUM>, for example, as a detached and/or detachable spectrometer. Alternately and/or additionally, the filter array spectrometer <NUM> and/or the spectrum generator <NUM> may be integrated components of a host platform such as, for example, a smartphone, a tablet personal computer (PC), laptop, a robot, a drone, and/or a wearable device (e.g., smartwatch, fitness tracker, and/or the like). For instance, the filter array spectrometer <NUM> and the spectrum generator <NUM> may both be integrated into the host platform such that the host platform may serve as a standalone spectrometer.

In some example embodiments, the filter array spectrometer <NUM> may be configured to generate a plurality of transmission patterns associated with light passing through the filter array spectrometer <NUM>. For instance, the filter array spectrometer <NUM> may include a plurality of filters that forms, for example, a filter array. The plurality of filters may be etalons of varying thickness. It should be appreciated that an etalon may include a pair of partially reflective surfaces and the thickness of the etalon may correspond to a distance between the pair of partially reflective surfaces.

In some example embodiments, an etalon may be configured to transmit only some wavelengths of the light (e.g., from the original spectrum of light) passing through the etalon, thereby forming a transmission pattern. This transmission pattern may include multiple transmission peaks that correspond to the wavelengths of light (e.g., from the original spectrum of light) that are able to pass through the etalon. Moreover, this transmission pattern may correspond to the thickness of the etalon as well as the reflectivity of the reflective surfaces forming the etalon. Thus, the same light passing through etalons having different thicknesses may generate different transmission patterns that are unique to each etalon.

In some example embodiments, the filter array spectrometer <NUM> may further include a sensor configured to capture the transmission pattern from each filter in the filter array. The sensor may be an image sensor and/or a light intensity detector. For instance, the sensor <NUM> may be a charge-coupled device (CCD) sensor, a complementary metal-oxide semiconductor (CMOS) sensor, a thermal sensor, a photodiode, an avalanche photo detector (APD), a photomultiplier tube (PMT), and/or the like.

In some example embodiments, the spectrum generator <NUM> may be configured to reconstruct the original spectrum of the light passing through the filter array spectrometer <NUM>. Each filter (e.g., etalon) in the filter array forming the filter array spectrometer <NUM> may provide a transmission pattern (e.g., captured by the sensor) that is unique to that filter. For instance, the same light may pass through filters (e.g., etalons) having different thicknesses, thereby generating different transmission patterns at each filter. Each transmission pattern may include transmission peaks that correspond to wavelengths that are part of the original spectrum of the light. These different transmissions patterns may be used to reconstruct the original spectrum of light passing through the filter array spectrometer <NUM>.

In some example embodiments, the reconstructed spectrum of the light passing through the filter array spectrometer <NUM> may be used to analyze an object emitting, reflecting, and/or transmitting the light. As noted earlier, the object may emit, reflect, and/or transmit light with and/or without an active external light source. According to some example embodiments, the object may emit, reflect, and/or transmit light (e.g., in the mid-infrared range) that may be specific to the molecules present in the object. Here, the spectrum of light emitted, reflected, and/or transmitted by the object may serve as a spectral signature that may be used to determine the molecular composition of the object (e.g., the sugar, fact, and/or protein content of a food item). Thus, the molecular composition of the object may be determined by at least identifying, in a data store <NUM> storing a plurality of spectral signatures of known molecular compositions, a spectral signature that is a match to the reconstructed spectrum. Alternately and/or additionally, the object may emit, reflect, and/or transmit thermal electromagnetic radiation (e.g., black-body radiation in the mid-infrared range) that may be used for passive thermal vision and/or temperature measurements.

<FIG> depicts an example configuration of the filter array spectrometer <NUM>, in accordance with some example embodiments. Referring to <FIG>, the filter array spectrometer <NUM> may include a selectable filter wheel <NUM> and a sensor <NUM>. As shown in <FIG>, the filter array spectrometer <NUM> may be configured with a single sensor (e.g., the sensor <NUM>) that is capable of capturing the transmission pattern from one filter at a time. Thus, in accordance with some example embodiments, the selectable filter wheel <NUM> may be configured to couple a single filter, such as an etalon, with the sensor <NUM> at a time. For instance, the selectable filter wheel <NUM> may be rotated to place a single filter (e.g., etalon) before the sensor <NUM>, thereby enabling the sensor <NUM> to capture the transmission pattern from that one filter before the selectable filter wheel <NUM> may be rotated to place another filter (e.g., etalon) before the sensor <NUM>. It should be appreciated that the sensor <NUM> may be any image sensor and/or light intensity detector. For instance, the sensor <NUM> may be a charge-coupled device (CCD) sensor, a complementary metal-oxide semiconductor (CMOS) sensor, a thermal sensor, a photodiode, an avalanche photo detector (APD), a photomultiplier tube (PMT), and/or the like.

Referring again to <FIG>, the filter array spectrometer <NUM> may further include one or more optics <NUM>. The one or more optics <NUM> may be, for example, optical lenses and/or mirrors configured to control the incident angle and/or focus of the incoming light with respect to the filters in the selectable filter wheel <NUM>. Furthermore, as shown in <FIG>, the filter array spectrometer <NUM> may include a housing <NUM>. The one or more optics <NUM>, the selectable filter wheel <NUM>, and/or the sensor <NUM> may be encased within the housing <NUM>. According to some example embodiments, the housing <NUM> may be configured to enable the filter array spectrometer <NUM> to serve as a detached and/or detachable spectrometer. Alternately and/or additionally, the housing <NUM> may be configured to enable the filter array spectrometer <NUM> to be an integrated component of a host platform (e.g., a smartphone, a tablet personal computer, laptop, a robot, a drone, a wearable device, and/or the like).

<FIG> depicts another example configuration of the filter array spectrometer <NUM>, in accordance with some example embodiments. Referring to <FIG> and <FIG>, the filter array spectrometer <NUM> may include a filter array <NUM> and a sensor array156. The filter array <NUM> may be, for example, an array of etalons having varying thicknesses. As shown in <FIG>, the filter array spectrometer <NUM> may be configured with an array of sensors, such as the sensor array <NUM>, that is capable of capturing the transmission pattern from multiple filters (e.g., etalons) at once. Thus, in accordance with some example embodiments, the filter array <NUM> may be placed before the sensor array <NUM> to enable the sensor array <NUM> to capture transmission patterns from a plurality of filters in the filter array <NUM>. It should be appreciated that the sensor array <NUM> may be formed from a plurality of image sensors and/or light intensity detector. For example, the sensor array <NUM> may include a plurality of charge-coupled device (CCD) sensors, complementary metal-oxide semiconductor (CMOS) sensors, thermal sensors, photodiodes, avalanche photo detectors (APD), photomultiplier tubes (PMT), and/or the like.

Referring again to <FIG>, the filter array spectrometer <NUM> may further include one or more optics <NUM>. The one or more optics <NUM> may be, for example, optical lenses and/or mirrors configured to control the incident angle and/or focus of the incoming light with respect to the filter array <NUM>. Furthermore, as shown in <FIG>, the filter array spectrometer <NUM> may include a housing <NUM>. The one or more optics <NUM>, the filter array <NUM>, and/or the sensor array <NUM> may be encased within the housing <NUM>. According to some example embodiments, the housing <NUM> may be configured to enable the filter array spectrometer <NUM> to serve as a detached and/or detachable spectrometer. Alternately and/or additionally, the housing <NUM> may be configured to enable the filter array spectrometer <NUM> to be an integrated component of a host platform (e.g., a smartphone, a tablet personal computer, laptop, a robot, a drone, a wearable device, and/or the like).

<FIG> depicts a perspective view of the filter array <NUM> and the sensor array <NUM>, in accordance with some example embodiments. The filter array <NUM> may be an array of etalons having varying thicknesses. Referring to <FIG> and <FIG>, the filter array <NUM> may be a <NUM> × <NUM> grid structure having <NUM> separate filters such as etalons. However, it should be appreciated that the filter array <NUM> may include any number of separate filters. Moreover, the filters forming the filter array <NUM> arranged in any pattern in addition to and/or instead of the grid structure shown in <FIG>.

In some example embodiments, the filter array <NUM> may be positioned before the sensor array <NUM> such that transmission patterns formed by incoming light passing through the filter array <NUM> may be captured by the sensor array <NUM>. For instance, as shown in <FIG>, the filter array <NUM> may include a plurality of filters including, for example, a first filter <NUM> and a second filter <NUM>. The first filter <NUM> and the second filter <NUM> may be etalons having different thicknesses and thus different optical properties. Meanwhile, the sensor array <NUM> may include a plurality of sensors including, for example, a first sensor <NUM> and a second sensor <NUM>. The first sensor <NUM> and the second sensor <NUM> may be charge-coupled device (CCD) sensors and/or complementary metal-oxide semiconductor (CMOS) sensors.

In some example embodiments, the first sensor <NUM> may be configured to capture the transmission pattern formed by the incoming light passing through the first filter <NUM> while the second sensor <NUM> may be configured to capture the transmission pattern of the incoming light passing through the second filter <NUM>. It should be appreciated that the first filter <NUM> may have a different thickness than the second filter <NUM>. This variation in the thickness may cause the incoming light passing through the first filter <NUM> to form a different transmission pattern than the incoming light passing through the second filter <NUM>. The different transmission patterns maybe used (e.g., by the spectrum generator <NUM>) to reconstruct the original spectrum of the incoming light.

<FIG> depict input options for the filter array spectrometer <NUM>, in accordance with some example embodiments. As shown in <FIG>, in some example embodiments, the filter array spectrometer <NUM> may be configured to directly capture incoming light. Alternately and/or additionally, the filter array spectrometer <NUM> may be configured to capture incoming light via a fiber optics port <NUM>. It should be appreciated that the filter array spectrometer <NUM> may be configured to capture incoming light in any manner.

<FIG> depicts the first filter <NUM> and the second filter <NUM>, in accordance with some example embodiments. Referring to <FIG> and <FIG>, the first filter <NUM> and the second filter <NUM> may form at least a portion of the selectable filter wheel <NUM> described with respect to <FIG> and/or the filter array <NUM> described with respect to <FIG>.

As shown in <FIG>, the first filter <NUM> and the second filter <NUM> may be etalons formed from a pair of reflective surfaces separated by an optically transparent medium. For instance, the first filter <NUM> may include a first reflective surface <NUM> and a second reflective surface <NUM> that are separated by a first optically transparent medium <NUM>. Meanwhile, the second filter <NUM> may include a third reflective surface <NUM> and a fourth reflective surface <NUM> that are separated by a second optically transparent medium <NUM>. In some example embodiments, the reflective surfaces forming the first filter <NUM> and/or the second filter <NUM> may be partially reflective. Thus, the first reflective surface <NUM>, the second reflective surface <NUM>, the third reflective surface <NUM>, and/or the fourth reflective surface <NUM> may be associated with a reflectivity R. It should be appreciated that the reflectivity R of a reflective surface may correspond to a portion of the incoming light that may be reflected by the reflective surface and/or a portion of the incoming light that may be allowed to pass through the reflective surface.

According to some example embodiments, the first reflective surface <NUM>, the second reflective surface <NUM>, the third reflective surface <NUM>, and/or the fourth reflective surface <NUM> may be formed from a metallic film including, for example, silver (Ag), gold (Au), aluminum (Al), and/or the like. The metallic film may have a thickness of <NUM> nanometers (nm) and/or optimized different thickness. The first optically transparent medium <NUM> and/or the second optically transparent medium <NUM> may be formed from a <NUM> nanometer thick layer of silicon dioxide (SiOz).

In some example implementations, the first filter <NUM> and/or the second filter <NUM> may be a part of a <NUM> × <NUM> filter array. However, it should be appreciated that the first filter <NUM> and/or the second filter <NUM> may be part of any N × M filter array, where N and M may be a same or different arbitrary numbers. To form this <NUM> × <NUM> filter array, a <NUM> nanometer layer of silver (Ag) may first be deposited on a glass substrate using sputtering deposition while a <NUM> nanometer layer of silicon dioxide (SiO<NUM>) may be subsequently deposited thereon using plasma-enhanced chemical vapor deposition. A <NUM> × <NUM> grid step structure may be formed from poly(methyl methacrylate) (PMMA) by at least spin-coating a <NUM> micron thick layer of poly(methyl methacrylate) on top of the silicon dioxide and then depositing a <NUM> micron thick layer of conductive gold (Au) thereon. The resulting structure (e.g., a <NUM> × <NUM> grid of squares having dimensions of <NUM> × <NUM> microns) may be placed in an electron beam lithography machine and exposed to a varying electron beam dose, which may range from <NUM> to <NUM> micro-Colombes per square centimeter (µC/cm<NUM>) at an energy of <NUM> kiloelectronvolt (keV). The gold (Au) may be subsequently removed using a potassium iodide (KI) etchant while the poly(methyl methacrylate) may be developed by submerging the poly(methyl methacrylate) grid structure in a solution of methyl isobutyl ketone (MIBK) for <NUM> minutes and rinsing with isopropyl alcohol for <NUM> seconds. This may result in a <NUM> by <NUM> array of recesses (e.g., within the poly(methyl methacrylate)) that range in depth from <NUM> nanometers to <NUM> microns. Here, the poly(methyl methacrylate) grid structure may be dried under nitrogen gas (N<NUM>) and finished with an additional <NUM> nanometer layer of silver (e.g., applied via sputter deposition) and a <NUM> nanometer layer of silicon dioxide serving as a protective film to prevent oxidation of the silver. The resulting <NUM> × <NUM> filter array may include filters (e.g., the first filter <NUM> and/or the second filter <NUM>) that range in thickness between <NUM> microns to <NUM> microns.

<FIG> depicts the filter array <NUM>, in accordance with some example embodiments. Referring to <FIG>, the filter array <NUM> may be a <NUM> millimeter by <NUM> millimeter structure with <NUM> filters that form a <NUM> × <NUM> grid. For scale, <FIG> depicts the filter array <NUM> next to a dime. Meanwhile, <FIG> shows the filter array <NUM> being back-illuminated by room fluorescent lighting. As shown in <FIG>, owing to differences in filter thickness and the resulting transmission pattern, color transmission may vary from filter to filter.

In some example embodiments, the first filter <NUM> may have a different thickness than the second filter <NUM>. The respective thicknesses of the first filter <NUM> and the second filter <NUM> may correspond to a distance separating the reflective surfaces forming the first filter <NUM> and the second filter <NUM>. As shown in <FIG>, the first reflective surface <NUM> and the second reflective surface <NUM> (e.g., forming the first filter <NUM>) may be separated by a first distance d<NUM>. Meanwhile, the third reflective surface <NUM> and the fourth reflective surface <NUM> (e.g., forming the second filter <NUM>) may be separated by a second distance d<NUM>. Incoming light passing through a filter (e.g., etalon) may form a transmission pattern as the reflective surfaces may cause the incoming light to interfere with itself by at least reflecting some portions of the light while transmitting other portions of the light. In particular, the transmission pattern may include periodic transmission peaks resulting from constructive interference between portions of the light being reflected by the reflective surfaces.

<FIG> depicts a graph illustrating transmission patterns associated with the first filter <NUM> and the second filter <NUM>, in accordance with some example embodiments. Referring to <FIG> and <FIG>, the transmission patterns associated with the first filter <NUM> and the second filter <NUM> may be captured by filter array <NUM> (e.g., the first sensor <NUM> and the second sensor <NUM>). <FIG> shows a first transmission pattern <NUM> corresponding to the transmission pattern of light passing through the first filter <NUM> and a second transmission pattern <NUM> corresponding to the transmission pattern of light passing through the second filter <NUM>. As noted above, the difference in the respective thicknesses of the first filter <NUM> and the second filter <NUM> may cause light passing through the first filter <NUM> to form a different transmission pattern than the same light passing through the second filter <NUM>. In particular, the positions of the transmission peaks within the first transmission pattern <NUM> may differ from the positions of the transmission peaks within the second transmission pattern <NUM> due to the differences in the thickness of the first filter <NUM> and the second filter <NUM>.

In some example embodiments, the first transmission pattern <NUM> may correspond to the wavelengths of light that is able to pass through the first filter <NUM> while the second transmission pattern <NUM> may correspond to the wavelengths of light that is able to pass through the second filter <NUM>. Thus, the first transmission pattern <NUM> and the second transmission pattern <NUM> may each provide a respective sampling of the original spectrum of the light passing through the first filter <NUM> and the second filter <NUM>.

It should be appreciated that the transmission pattern of a filter (e.g., etalon) may correlate with the reflectivity of the reflective surfaces as well the thickness of the filter (e.g., the distance between the reflective surfaces). Thus, in some example embodiments, the first filter <NUM> and the second filter <NUM> may be configured with different thicknesses such that the first transmission pattern <NUM> is different from the second transmission pattern <NUM>. The first transmission pattern <NUM> may be different from the second transmission pattern <NUM>, when at least one transmission peak in the first transmission pattern <NUM> does not overlap with a transmission peak in the second transmission pattern <NUM>. Alternately and/or additionally, the reflectivity of the surfaces forming the first filter <NUM> and the second filter <NUM> may be configured (e.g., to different values) such that the first transmission pattern <NUM> is different from the second transmission pattern <NUM>.

In some example embodiments, the transmission pattern Ti for a filter i (e.g., in the selectable filter wheel <NUM> and/or the filter array <NUM>) may be defined by the following equation (<NUM>): <MAT> wherein λ may be the wavelength of the light incident at a normal angle on the filter (e.g., the first filter <NUM> and/or the second filter <NUM>), R may be the reflectivity of the reflective surfaces forming the filter, d may be a distance between the reflective surfaces forming the filter, and n may be the refractive index of the optically transparent medium separating the reflective surfaces.

In some example embodiments, a sensor (e.g., first sensor <NUM>, the second sensor <NUM>) may detect, from a filter (e.g., the first filter <NUM>, the second filter <NUM>), a signal that corresponds to the transmission pattern formed by incoming light passing through the filter. The signal Ii for a filter i (e.g., in the filter array <NUM>) may be defined by the following equation (<NUM>): <MAT> wherein i = <NUM>, <NUM>,. m, m may correspond to a total number of filters (e.g., in the selectable filter wheel <NUM> and/or the filter array <NUM>), and S(λ) may a spectrum of the light incident on the filter i.

In some example embodiments, the signal Ii obtained at the filter i may correspond to the transmission pattern Ti formed by the light passing through the filter i. Thus, the original spectrum S may be recovered based at least on the individual transmission patterns Ti at each filter i. For instance, one or more signal reconstruction techniques may be applied in order to determine a reconstructed spectrum S' that best fits the signals Ii obtained from each of the m number of filters (e.g., in the selectable filter wheel <NUM> and/or the filter array <NUM>).

When a compressive sensing signal reconstruction technique is applied to reconstruct the original spectrum <NUM>, minimization of the L1 norm may converge to a sparse solution for the reconstructed spectrum S'. As such, a compressive sensing signal reconstruction technique may be suitable when the filter array is relatively small (e.g., when m is a relatively small value) and/or the original spectrum <NUM> is sufficiently sparse to be reconstructed based on relatively few measurements of the incoming light.

The fidelity of reconstructed spectrum S' (e.g., with respect to the original spectrum S) may be dependent on the number m of the signals Ii and/or the transmission patterns Ti used to generate the reconstructed spectrum S'. Thus, a total number of filters (e.g., etalons) in the selectable filter wheel <NUM> and/or the filter array <NUM> may limit the fidelity of the reconstructed spectrum S'. Moreover, this limit on reconstruction fidelity may be further related to the sparsity of the original spectrum S, which may correspond to a number of wavelength components in the original spectrum S that are at or near zero. Accordingly, some signal reconstruction techniques (e.g., compressive sensing) may be especially suitable for recovering a sparse spectrum from a relatively few number of measurements. To further illustrate, the spectrum of a laser is extremely sparse in wavelength, being nearly monochromatic. Thus, the original spectrum of a laser may be accurately reconstructed using compressive sensing and a small number of measurements. By contrast, the spectrum for white noise may be extremely dense, thereby preventing the spectrum for white noise from being reconstructed to a high fidelity using compressing sensing and a small number of measurements.

The number m of filters in the selectable filter wheel <NUM> and/or the filter array <NUM> may be determined based on the sparsity of the original spectrum S. For instance, the selectable filter wheel <NUM> and/or the filter array <NUM> may include a threshold number of filters (e.g., etalons) required to achieve a required level of reconstruction fidelity. This threshold number of filters may vary depending on the sparsity of the original spectrum <NUM> that requires reconstruction. It should be appreciated that the selectable filter wheel <NUM> and/or the filter array <NUM> may include a larger number of filters when the original spectrum S is dense. By contrast, the selectable filter wheel <NUM> and/or the filter array <NUM> may include a smaller number of filters when the original spectrum <NUM> is sparse.

The spectral resolution of the reconstructed spectrum S may correspond to the thickness of the filters (e.g., the first filter <NUM>, the second filter <NUM>) in the selectable filter wheel <NUM> and/or the filter array <NUM>. Here, the quality factor (Q-factor) of a filter (e.g., etalon) and the sharpness of the transmission peaks (e.g., in a transmission pattern) may be in direct correlation with the thickness of the filter. That is, the sharpness of the transmission peaks (e.g., in a transmission pattern) may correspond to the sharpness of a point-spread function. Thus, a thicker filter (e.g., etalon) may provide transmission peaks having a finer full-width half maximum (FWHM) and a higher resolution reconstructed spectrum. It should be appreciated that some signal reconstruction techniques may be able to compensate for a limit in spectral resolution imposed by the thickness of the available filters. For instance, compressive sensing may enable a highly accurate recovery of a sparse spectrum, despite resolution limits imposed by the available filters.

The filter array spectrometer <NUM> may be calibrated. For instance, the filter array spectrometer <NUM> may be calibrated in order to correct for a non-uniform illumination of the filter array <NUM> (e.g., due to the collimating of the incoming light). Moreover, the filter array spectrometer <NUM> may be calibrated based on one or more known spectra. A correction factor may be generated based on a difference between the known spectra and the spectra measured by the filter array spectrometer <NUM>. The correction factor may correspond to an average deviation between the known spectra and the spectra measured by the filter array spectrometer <NUM>. This correction factor may be applied to subsequent measurements taken using the filter array spectrometer <NUM>.

<FIG> depicts a flowchart illustrating a process <NUM> for reconstructive spectrometry, in accordance with some example embodiments. Referring to <FIG>, the process <NUM> may be performed by the reconstructive spectrometry system <NUM>.

The reconstructive spectrometry system <NUM> may generate the first transmission pattern <NUM> by at least processing light using the first filter <NUM> and the second transmission pattern <NUM> by at least processing the light using the second filter <NUM> (<NUM>). For instance, the reconstructive spectrometry system <NUM> may include the filter array spectrometer <NUM>. The filter array spectrometer <NUM> may include the first filter <NUM> and the second filter <NUM>. Light passing through the first filter <NUM> may the first transmission pattern <NUM> while the same light passing through the second filter <NUM> may generate the second transmission pattern <NUM>. The first transmission pattern <NUM> and the second transmission pattern <NUM> may differ in at least the positions of one or more transmission peaks within the first transmission pattern <NUM> and the second transmission pattern <NUM>. It should be appreciated that the differences between the first transmission pattern <NUM> and the second transmission pattern <NUM> may correspond to differences in the respective thicknesses of the first filter <NUM> and the second filter <NUM>.

The reconstructive spectrometry system <NUM> may determine, based at least on the first transmission pattern and the second transmission pattern, a spectrum of the incoming light (<NUM>). In some example embodiments, the reconstructive spectrometry system <NUM> (e.g., the spectrum generator <NUM>) may reconstruct the original spectrum of the incoming light based at least on the first transmission pattern <NUM> and the second transmission pattern <NUM>. For instance, the reconstructive spectrometry system <NUM> may apply one or more signal reconstruction techniques (e.g., compressive sensing) to at least determine an approximation of the original spectrum that best fits the first transmission pattern <NUM> and the second transmission pattern <NUM>.

Table <NUM> below shows pseudo program code implementing the operations of the reconstructive spectrometry system <NUM>. For instance, Table <NUM> shows pseudo program code for calibrating of the reconstructive spectrometry system <NUM>, the collection of measurements (e.g., transmission patterns) taken at each filter (e.g., in the selectable filter wheel <NUM> and/or the filter array <NUM>), and for reconstructing the original spectrum S.

<FIG> depicts a block diagram illustrating a computing system <NUM> consistent with implementations of the current subject matter. Referring to <FIG> and <FIG>, the computing system <NUM> can be used to implement the spectrum generator <NUM> and/or any components therein.

As shown in <FIG>, the computing system <NUM> can include a processor <NUM>, a memory <NUM>, a storage device <NUM>, and input/output devices <NUM>. The processor <NUM>, the memory <NUM>, the storage device <NUM>, and the input/output devices <NUM> can be interconnected via a system bus <NUM>. The processor <NUM> is capable of processing instructions for execution within the computing system <NUM>. Such executed instructions can implement one or more components of, for example, the spectrum generator <NUM>. In some implementations of the current subject matter, the processor <NUM> can be a single-threaded processor. Alternately, the processor <NUM> can be a multi-threaded processor. The processor <NUM> is capable of processing instructions stored in the memory <NUM> and/or on the storage device <NUM> to display graphical information for a user interface provided via the input/output device <NUM>.

The memory <NUM> is a computer readable medium such as volatile or nonvolatile that stores information within the computing system <NUM>. The memory <NUM> can store data structures representing configuration object databases, for example. The storage device <NUM> is capable of providing persistent storage for the computing system <NUM>. The storage device <NUM> can be a floppy disk device, a hard disk device, an optical disk device, or a tape device, or other suitable persistent storage means. The input/output device <NUM> provides input/output operations for the computing system <NUM>. In some implementations of the current subject matter, the input/output device <NUM> includes a keyboard and/or pointing device. In various implementations, the input/output device <NUM> includes a display unit for displaying graphical user interfaces.

According to some implementations of the current subject matter, the input/output device <NUM> can provide input/output operations for a network device. For example, the input/output device <NUM> can include Ethernet ports or other networking ports to communicate with one or more wired and/or wireless networks (e.g., a local area network (LAN), a wide area network (WAN), the Internet).

In some implementations of the current subject matter, the computing system <NUM> can be used to execute various interactive computer software applications that can be used for organization, analysis and/or storage of data in various (e.g., tabular) format (e.g., Microsoft Excel®, and/or any other type of software). Alternatively, the computing system <NUM> can be used to execute any type of software applications. These applications can be used to perform various functionalities, e.g., planning functionalities (e.g., generating, managing, editing of spreadsheet documents, word processing documents, and/or any other objects, etc.), computing functionalities, communications functionalities, etc. The applications can include various add-in functionalities or can be standalone computing products and/or functionalities. Upon activation within the applications, the functionalities can be used to generate the user interface provided via the input/output device <NUM>. The user interface can be generated and presented to a user by the computing system <NUM> (e.g., on a computer screen monitor, etc.).

These computer programs, which can also be referred to as programs, software, software applications, applications, components, or code, include machine instructions for a programmable processor, and can be implemented in a high-level procedural and/or object-oriented programming language, and/or in assembly/machine language. The machine-readable medium can alternatively, or additionally, store such machine instructions in a transient manner, such as for example, as would a processor cache or other random access memory associated with one or more physical processor cores.

To provide for interaction with a user, one or more aspects or features of the subject matter described herein can be implemented on a computer having a display device, such as for example a cathode ray tube (CRT) or a liquid crystal display (LCD) or a light emitting diode (LED) monitor for displaying information to the user and a keyboard and a pointing device, such as for example a mouse or a trackball, by which the user may provide input to the computer. For example, feedback provided to the user can be any form of sensory feedback, such as for example visual feedback, auditory feedback, or tactile feedback; and input from the user may be received in any form, including, but not limited to, acoustic, speech, or tactile input. Other possible input devices include, but are not limited to, touch screens or other touch-sensitive devices such as single or multi-point resistive or capacitive track pads, voice recognition hardware and software, optical scanners, optical pointers, digital image capture devices and associated interpretation software, and the like.

Claim 1:
A system, comprising:
an etalon array (<NUM>) having a first etalon (<NUM>) and a second etalon (<NUM>), the first etalon (<NUM>) having a first pair of at least partially reflective surfaces (<NUM>, <NUM>) and being configured to process light to at least generate a first transmission pattern (<NUM>), the first transmission pattern (<NUM>) having at least a first transmission peak corresponding to a first wavelength in an original spectrum of the light, the second etalon (<NUM>) having a second pair of at least partially reflective surfaces (<NUM>, <NUM>), the second pair being separate from the first pair such as to form separate filters, the second etalon (<NUM>) being configured to process the light to at least generate a second transmission pattern (<NUM>), the second transmission pattern (<NUM>) having at least a second transmission peak corresponding to a second wavelength in the original spectrum of the light, the first etalon (<NUM>) having a different thickness than the second etalon (<NUM>) in order for the first transmission pattern (<NUM>) to have at least one transmission peak that is at a different wavelength than the second transmission pattern (<NUM>), and
at least one data processor; and
at least one memory including program code which, when executed by the at least one data processor, provides operations comprising:
reconstructing, based at least on the first transmission pattern (<NUM>) and the second transmission pattern (<NUM>), the original spectrum of the light, the original spectrum of the light being reconstructed by at least applying one or more signal reconstruction techniques to determine an approximate spectrum of the light that best fits the first transmission pattern (<NUM>) and the second transmission pattern (<NUM>); and
analyzing, based at least on the reconstructed spectrum of the light, an object emitting, reflecting, and/or transmitting the light to at least determine a molecular composition and/or a temperature of the object, the analyzing of the object including comparing the reconstructed spectrum of the light to a plurality of known spectra.