Abstract: A method for retrieving a corrected spectrum from a measured spectrum (e.g., retrieving a top-of-water spectrum from a measured top-of-atmosphere spectrum) includes creating a scene-specific model of a region of interest and performing a ray-tracing simulation to simulate rays of light that would reach an airborne (or spaceborne) sensor. The region of interest can be an optically complex area such as an inland or coastal body of water. Based on the ray-tracing simulation, a scene-specific correction for unwanted effects (e.g., adjacency effects, variable atmospheric conditions, and/or other suitable effects) is obtained. A corrected spectrum is obtained by correcting the measured spectrum using the scene-specific correction. The ray-tracing simulation may be performed using a graphical processing unit, allowing the scene-specific correction to be performed in real time or near real time.

Abstract: A hyperspectral sensing device may include an optical collector configured to collect light and to transfer the collected light to a sensor having spectral resolution sufficient for sensing hyperspectral data. In some examples, the sensor comprises a compact spectrometer. The device further comprises a power supply, an electronics module, and an input/output hub enabling the device to transmit acquired data (e.g., to a remote server). In some examples, a plurality of hyperspectral sensing devices are deployed as a network to acquire data over a relatively large area. Methods are disclosed for performing dark-current calibration and/or radiometric calibration on data obtained by the hyperspectral sensing device, and/or another suitable device. Data obtained by the device may be represented in a functional basis space, enabling computations that utilize all of the hyperspectral data without loss of information.

Abstract: A hyperspectral sensing device may include an optical collector configured to collect light and to transfer the collected light to a sensor having spectral resolution sufficient for sensing hyperspectral data. In some examples, the sensor comprises a compact spectrometer. The device further comprises a power supply, an electronics module, and an input/output hub enabling the device to transmit acquired data (e.g., to a remote server). In some examples, a plurality of hyperspectral sensing devices are deployed as a network to acquire data over a relatively large area. Methods are disclosed for performing dark-current calibration and/or radiometric calibration on data obtained by the hyperspectral sensing device, and/or another suitable device. Data obtained by the device may be represented in a functional basis space, enabling computations that utilize all of the hyperspectral data without loss of information.

Abstract: A hyperspectral sensing device may include an optical collector configured to collect light and to transfer the collected light to a sensor having spectral resolution sufficient for sensing hyperspectral data. In some examples, the sensor comprises a compact spectrometer. The device further comprises a power supply, an electronics module, and an input/output hub enabling the device to transmit acquired data (e.g., to a remote server). In some examples, a plurality of hyperspectral sensing devices are deployed as a network to acquire data over a relatively large area. Methods are disclosed for performing dark-current calibration and/or radiometric calibration on data obtained by the hyperspectral sensing device, and/or another suitable device. Data obtained by the device may be represented in a functional basis space, enabling computations that utilize all of the hyperspectral data without loss of information.

Abstract: A method for retrieving a corrected spectrum from a measured spectrum (e.g., retrieving a top-of-water spectrum from a measured top-of-atmosphere spectrum) includes creating a scene-specific model of a region of interest and performing a ray-tracing simulation to simulate rays of light that would reach an airborne (or spaceborne) sensor. The region of interest can be an optically complex area such as an inland or coastal body of water. Based on the ray-tracing simulation, a scene-specific correction for unwanted effects (e.g., adjacency effects, variable atmospheric conditions, and/or other suitable effects) is obtained. A corrected spectrum is obtained by correcting the measured spectrum using the scene-specific correction. The ray-tracing simulation may be performed using a graphical processing unit, allowing the scene-specific correction to be performed in real time or near real time.

Abstract: A hyperspectral sensing device may include an optical collector configured to collect light and to transfer the collected light to a sensor having spectral resolution sufficient for sensing hyperspectral data. In some examples, the sensor comprises a compact spectrometer. The device further comprises a power supply, an electronics module, and an input/output hub enabling the device to transmit acquired data (e.g., to a remote server). In some examples, a plurality of hyperspectral sensing devices are deployed as a network to acquire data over a relatively large area. Methods are disclosed for performing dark-current calibration and/or radiometric calibration on data obtained by the hyperspectral sensing device, and/or another suitable device. Data obtained by the device may be represented in a functional basis space, enabling computations that utilize all of the hyperspectral data without loss of information.

Abstract: An excitation signal generator (“ESG”) is described. The ESG generates an minimized excitation signal for use in a test system to generate a functional model of a device under test (“DUT”) where extreme values of the minimized excitation signal are increased toward a central value without changing the power spectrum at the DUT.

Abstract: A method generating a digital waveform, pulse generators and VNAs based thereon are disclosed. The digital waveform is generated in response to user-supplied parameters defining a sawtooth chirp signal. A digital baseband chirp signal that depends on the input parameters is first generated and then the digital baseband signal is upconverted to a center frequency to form an upconverted chirp signal. The upconverted chirp signal is then converted to an M-ary signal having M levels and then (optionally) filtered through a band pass filter to attenuate frequency components of the digital chirp signal outside a predetermined band of frequencies. The digital baseband chirp signal can also include the sum of first and second chirp signals having amplitudes and phase determined to reduce variations in amplitude as a function of frequency in a predetermined band of frequencies.

Abstract: A mixer measurement system and method use a chaotic signal to characterize a mixer under test. The mixer measurement system includes a chaotic reference source, an excitation source at an input end of the mixer under test and an inverse system at an output end of the mixer under test. The inverse system removes a chaotic component from a response signal from the stimulated mixer under test to produce a recovered signal having an included distortion that is characteristic of the mixer under test. The method of characterizing a mixer includes applying the chaotic stimulation to the mixer under test to obtain a response signal and employing the inverse system to remove the chaotic component from the response signal.

Abstract: An excitation signal generator (“ESG”) is described. The ESG generates an minimized excitation signal for use in a test system to generate a functional model of a device under test (“DUT”) where extreme values of the minimized excitation signal are increased toward a central value without changing the power spectrum at the DUT.

Abstract: A measurement system, a chaotic lock-in amplifier, and methods use chaotic lock-in amplification to measure a stimulus response from one or more of a device under test, a sample under test and a system under test. The measurement system includes a chaotic reference source, a chaotic excitation source and a chaotic lock-in amplifier to facilitate detection of a chaotic response signal from the respective item(s) under test. A chaotic lock-in amplifier includes an inverse system that removes a chaotic component from the chaotic response signal. A method of measuring a response to a stimulation includes using the chaotic reference signal to achieve chaotic lock-in amplification that preferentially removes a chaotic component from the chaotic response signal.

Abstract: A tomographic reconstruction method and system incorporating Bayesian estimation techniques to inspect and classify regions of imaged objects, especially objects of the type typically found in linear, areal, or 3-dimensional arrays. The method and system requires a highly constrained model M that incorporates prior information about the object or objects to be imaged, a set of prior probabilities P(M) of possible instances of the object; a forward map that calculates the probability density P(D|M), and a set of projections D of the object. Using Bayesian estimation, the posterior probability p(M|D) is calculated and an estimated model MEST of the imaged object is generated. Classification of the imaged object into one of a plurality of classifications may be performed based on the estimated model MEST, the posterior probability p(M|D) or MAP function, or calculated expectation values of features of interest of the object.

Abstract: The model-based method tests compliance of production devices with the performance specifications of a device design. The production devices are manufactured in accordance with the device design by a manufacturing process. In the method, a simple model form based on the device design and the performance specifications is developed, a stimulus for testing the production devices is specified and each production device is tested. The model form has a basis function and model form parameters for the basis function. The model form parameters are dependent on the manufacturing process and differ in value among the production devices. A production device is tested by measuring the response of the production device to the stimulus; extracting, using the model form, the values of the model form parameters for the production device from the measured response and the stimulus; and checking compliance of the production device with the performance specifications using the extracted values of the model form parameters.

Abstract: A tomographic reconstruction method and system incorporating Bayesian estimation techniques to inspect and classify regions of imaged objects, especially objects of the type typically found in linear, areal, or 3-dimensional arrays. The method and system requires a highly constrained model M that incorporates prior information about the object or objects to be imaged, a set of prior probabilities P(M) of possible instances of the object; a forward map that calculates the probability density P(D|M), and a set of projections D of the object. Using Bayesian estimation, the posterior probability p(M|D) is calculated and an estimated model MEST of the imaged object is generated. Classification of the imaged object into one of a plurality of classifications may be performed based on the estimated model MEST, the posterior probability p(M|D) or MAP function, or calculated expectation values of features of interest of the object.