A miniaturized, lightweight turn-key hyperspectral sensor package incorporating a single, monolithic spectrograph, telescope and navigation system is being built for airborne applications on small, Unmanned Aircraft Systems (UAS). The sensor is based on Corning’s existing MicroHSI 410 Vis/NIR Selectable Hyperspectral Airborne Remote sensing Kit (SHARK) currently used for airborne agricultural monitoring. Under DOE sponsorship, we are extending the approach to cover the full spectral range from 0.4-2.5 microns with a single spectrograph. This will enable rapid aerial surveys of vegetative mass, quality, and carbon sequestration. Other applications include mineralogy, agriculture, and intelligence/surveillance/reconnaissance (ISR).
The sensor features an Offner-type spectrograph machined from a single transmissive block. The monolithic construction provides an unprecedented combination of high performance, low cost and low size, weight, and power. It has an f/1.4 aperture, 5 nm resolution, and measures only 46mm x 60mm x 76mm. The spectrograph block is coupled to a sterling-cooled, back-thinned, HgCdTe FPA covering 0.4-2.5 micron spectral range. The flight package, including spectrograph, camera, telescope, and navigation system weighs less than 2.4kg and can fit on group 1 UASs.
In this paper, we present the design and optical performance of the sensor, and a detailed physical model of detection performance in standard, airborne hyperspectral sensing applications. At 100 Hz data rate, the sensor will achieve shotnoise limited performance with SNR > 250 from 0.4-1.7 microns and SNR<100 between 2-2.3 microns. Operating procedures for airborne monitoring of vegetative properties are also discussed. Initial test flights on a UAS are scheduled for next summer.
Hyperspectral imaging (HSI) has been used for over two decades in laboratory research, academic, environmental and defense applications. In more recent time, HSI has started to be adopted for commercial applications in machine vision, conservation, resource exploration, and precision agriculture, to name just a few of the economically viable uses for the technology. Corning Incorporated (Corning) has been developing and manufacturing HSI sensors, sensor systems, and sensor optical engines, as well as HSI sensor components such as gratings and slits for over a decade and a half. This depth of experience and technological breadth has allowed Corning to design and develop unique HSI spectrometers with an unprecedented combination of high performance, low cost and low Size, Weight, and Power (SWaP). These sensors and sensor systems are offered with wavelength coverage ranges from the visible to the Long Wave Infrared (LWIR). The extremely low SWaP of Corning’s HSI sensors and sensor systems enables their deployment using limited payload platforms such as small unmanned aerial vehicles (UAVs).
This paper discusses use of the Corning patented monolithic design Offner spectrometer, the microHSI™, to build a highly compact 400-1000 nm HSI sensor in combination with a small Inertial Navigation System (INS) and micro-computer to make a complete turn-key airborne remote sensing payload. This Selectable Hyperspectral Airborne Remote sensing Kit (SHARK) has industry leading SWaP (1.5 lbs) at a disruptively low price due, in large part, to Corning’s ability to manufacture the monolithic spectrometer out of polymers (i.e. plastic) and therefore reduce manufacturing costs considerably. The other factor in lowering costs is Corning’s well established in house manufacturing capability in optical components and sensors that further enable cost-effective fabrication. The competitive SWaP and low cost of the microHSI™ sensor is approaching, and in some cases less than the price point of Multi Spectral Imaging (MSI) sensors. Specific designs of the Corning microHSI™ SHARK visNIR turn-key system are presented along with salient performance characteristics. Initial focus market areas include precision agriculture and historic and recent microHSI™ SHARK prototype test results are presented.
Hyperspectral imaging systems are finding broader applications in both the commercial and aerospace markets. It is becoming clear that to optimize the performance of these systems, their instrument transfer function needs to be tailored for each application. Vis-SWIR systems in the full 400nm to 2500nm waveband present particular design and manufacturing challenges. A single blazed grating is inadequate for a system operating in the full vis-SWIR wavelength range. In addition, optical materials and broad band coatings present a challenge for non-reflective systems. An understanding of the application and wavelengths of interest, combined with a judicious choice of a focal plane array, can then lead to an optimized system for the specific application. The ability to tailor the grating and manufacture a wide variety of grating profiles and substrate shapes becomes a significant performance enabler. This paper will discuss how the use of optical, coating, and grating design/analysis software, combined with grating manufacturing techniques assure meeting high performance requirements for different applications.
Hyperspectral imaging (HSI) is a technology that is rapidly transitioning from laboratory research and field demonstration to real-world deployment for a variety of applications. These applications include precision agriculture, manufacturing process monitoring, mineral and petroleum exploration, environmental management, disaster mitigation, defense intelligence/surveillance/reconnaissance for threat detection and identification, as well as a host of applications within the bio-medical field. Application-specific algorithms are continuously being developed to support the world-wide expanding use of HSI.
KEYWORDS: Detection and tracking algorithms, Target detection, Sensors, Visualization, Video, Algorithm development, Signal to noise ratio, Cameras, Acoustics, Visual system
Algorithms for synergistically fusing acoustic and optical sensory inputs, thereby mimicking biological attentional
processes are described. Manual existing perimeter defense surveillance systems using more than one sensory modality
combine different sensors' information to corroborate findings by other sensors and to add data from a second modality.
In contrast to how conventional systems work, animals use information from multiple sensory inputs in a way that
improves each sensory system's performance. We demonstrated that performance is enhanced when information in one
modality is used to focus processing in the other modality (a form of attention). This synergistic bi-modal operation
improves surveillance efficacy by focusing auditory and visual "attention" on a particular target or location.
Algorithms for focusing auditory and visual sensors using detection information were developed. These
combination algorithms perform "zoom-with-enhanced-acuity" in both the visual and auditory domains, triggered by
detection in either domain. Sensory-input processing algorithms focus on specific locations, indicated by at least one of
the modalities. This spatially focused processing emulates biological attention-driven focusing. We showed that given
information about the target, the acoustic algorithms were able to achieve over 80% correct target detection at signal-tonoise
ratios (SNRs) of -20 dB and above, as compared with similar performance at SNRs of -10 db and above without
target information from another modality. Similarly, the visual algorithm achieved performance of over 80% detection
with added noise variance of 0.001 without target indication, but maintained 100% detection at added noise variance of
0.05 when acoustic target information was taken into account.
An optical communication system suitable for voice communication, data retrieval from remote sensors and
identification had been designed, built and tested. The system design allows operation at ranges of several hundred
meters. The heart of the system is a modulated MEMS mirror that is electrostatically actuated and changes between a flat
reflective state and a corrugated diffractive state. A process for mass producing these mirrors at low cost was developed
and implemented. The mirror was incorporated as a facet in a hollow retro-reflector, allowing temporal modulation of an
interrogating beam and the return of the modulated beam to the interrogator. This modulator unit thus consists of a low
power, small and light communication node with large (about 60°) angular extent. The system's range and pointing are
determined by the interrogator /detector / demodulator unit (the transceiver), whereas the communicating node remains
small, low power and low cost. This transceiver is comprised of a magnified optical channel to establish line of sight
communication, an interrogating laser at 1550nm, an avalanche photo diode to detect the return signal and electronics to
drive the laser and demodulate the returned signal and convert it to an audio signal. Voice communication in free space
was demonstrated at ranges larger than 200 meters. A new retro-reflector design, incorporating more modulated mirrors
had been constructed. This configuration was built and tested. Its performance and advantages as compared to the single
mirror retro-reflector are discussed. An alternative system design that allows higher bandwidth data transmission is
described
Increasing battlefield awareness can improve both the effectiveness and timeliness of response in hostile military
situations. A system that processes acoustic data is proposed to handle a variety of possible applications. The front-end
of the existing biomimetic acoustic direction finding system, a mammalian peripheral auditory system model, provides
the back-end system with what amounts to spike trains. The back-end system consists of individual algorithms tailored to
extract specific information. The back-end algorithms are transportable to FPGA platforms and other general-purpose
computers. The algorithms can be modified for use with both fixed and mobile, existing sensor platforms.
Currently, gunfire classification and localization algorithms based on both neural networks and pitch are being developed
and tested. The neural network model is trained under supervised learning to differentiate and trace various gunfire
acoustic signatures and reduce the effect of different frequency responses of microphones on different hardware
platforms. The model is being tested against impact and launch acoustic signals of various mortars, supersonic and
muzzle-blast of rifle shots, and other weapons. It outperforms the cross-correlation algorithm with regard to
computational efficiency, memory requirements, and noise robustness. The spike-based pitch model uses the times
between successive spike events to calculate the periodicity of the signal. Differences in the periodicity signatures and
comparisons of the overall spike activity are used to classify mortar size and event type. The localization of the gunfire
acoustic signals is further computed based on the classification result and the location of microphones and other
parameters of the existing hardware platform implementation.
KEYWORDS: Digital signal processing, Analog electronics, Nerve, Neurons, Signal processing, Field programmable gate arrays, Acoustics, Mirrors, Computing systems, Electronics
We are developing low-power microcircuitry that implements classification and direction finding systems of very small
size and small acoustic aperture. Our approach was inspired by the fact that small mammals are able to localize sounds
despite their ears may be separated by as little as a centimeter. Gerbils, in particular are good low-frequency localizers,
which is a particularly difficult task, since a wavelength at 500 Hz is on the order of two feet. Given such signals, crosscorrelation-
based methods to determine direction fail badly in the presence of a small amount of noise, e.g. wind noise
and noise clutter common to almost any realistic environment. Circuits are being developed using both analog and
digital techniques, each of which process signals in fundamentally the same way the peripheral auditory system of
mammals processes sound. A filter bank represents filtering done by the cochlea. The auditory nerve is implemented
using a combination of an envelope detector, an automatic gain stage, and a unique one-bit A/D, which creates what
amounts to a neural impulse. These impulses are used to extract pitch characteristics, which we use to classify sounds
such as vehicles, small and large weaponry from AK-47s to 155mm cannon, including mortar launches and impacts. In
addition to the pitchograms, we also use neural nets for classification.
An optical communication system suitable for voice, data retrieval from remote sensors and identification is described.
The system design allows operation at ranges of several hundred meters. The heart of the system is a modulated MEMS
mirror that is electrostatically actuated and changes between a flat reflective state and a corrugated diffractive state. A
process for mass producing these mirrors at low cost was developed and is described. The mirror was incorporated as a
facet in a hollow retro-reflector, allowing temporal modulation of an interrogating beam and the return of the modulated
beam to the interrogator. This system thus consists of a low power, small and light communication node with large
(about 60°) angular extent. The system's range and pointing are determined by the interrogator /detector/demodulator
(Transceiver) unit. The transceiver is comprised of an optical channel to establish line of sight communication, an
interrogating laser at 1550nm, an avalanche photo diode to detect the return signal and electronics to drive the laser and
demodulate the detected signal and convert it to an audio signal. A functional prototype system was built using a
modified compact optical sight as the transceiver. Voice communication in free space was demonstrated. The design and
test of major components and the complete system are discussed.
This paper describes the flow of scientific and technological achievements beginning with a stationary "small, smart,
biomimetic acoustic processor" designed for DARPA that led to a program aimed at acoustic characterization and
direction finding for multiple, mobile platforms. ARL support and collaboration has allowed us to adapt the core
technology to multiple platforms including a Packbot robotic platform, a soldier worn platform, as well as a vehicle
platform. Each of these has varying size and power requirements, but miniaturization is an important component of the
program for creating practical systems which we address further in companion papers. We have configured the system to
detect and localize gunfire and tested system performance with live fire from numerous weapons such as the AK47, the
Dragunov, and the AR15. The ARL-sponsored work has led to connections with Natick Labs and the Future Force
Warrior program, and in addition, the work has many and obvious applications to homeland defense, police, and civilian needs.
Thermal recording with a laser beam is a promising process. More thermal recording applications in the graphic arts market and also in the medical and PCB imaging markets are surfacing in recent years. Thermal recording has advantages over traditional photographic recording in that it is dry and environmentally benign. Also thermal recording is a threshold process and therefore yields sharper images. Thermal recording media, however, require much higher powered lasers to record than conventional photographic media. We must therefore carefully determine the optimal parameters for recording thermally most efficiently. In this paper, we determine the minimum beam power requirements, in terms of recording media format, throughput and media sensitivity. We also analyze in this paper the spot profile required to achieve the optimal recording efficiency, assuming it is a controllable design parameter. Since the efficiency is not the only performance requirement from a recording system we discuss other important parameters of image quality which affect the spot profile and beam power choice for a thermal recording system.
The conventional approach to designing an imagesetter is to initially specify the subsystem design parameters
based on experience with similar existing systems. A breadboard model is then built and tested by extensively
inspecting photocopy output samples. Following the results of these image quality performance tests, the system
specification parameters are fine-tuned and a new breadboard model has to be built. Sometimes an additional
breadboard iteration is required for tolerancing.
We have developed an image fidelity simulation software package which, given the design parameters, simulates
the photocopy output to a high degree of agreement with the output of actual imagesetters. Consequently we adopted
a new approach to imagesetter system design in which we investigate the design parameter trade-offs and tolerances
before the first breadboard model is built, thereby significantly reducing development time and cost.
In this paper we define and discuss the image fidelity parameters, as would be measured on photocopy output.
We further describe the image simulation software functionality and analyze the dependence of the image fidelity
parameters on each of the system design parameters. We present a comparison between measured and simulated
results and discuss the design and tolerancing procedure using the simulation approach.
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