IERUS Technologies, under subcontract to Tethers Unlimited, is developing a machine vision inspection system for the validation of metallic components additively manufactured in space. The effort has begun with a survey of vision technologies, including stereo vision, structure from motion, light field imaging, and structured illumination. Using the optical data, 3D point clouds will be registered as the object is viewed from multiple orientations. From the point cloud data, a mix of deterministic and machine learning algorithms will be used to identify geometric primitives that can be compared to those included in the computer aided design model. In addition, the system will estimate the surface roughness. Based upon the tolerances required within the CAD, pass/fail criteria will be established and the system will determine if the part passes, fails, or cannot be determined. At the end of the current phase, IERUS will perform a demonstration using a prototype system on a challenge artifact provided by NASA.
A simulation study was conducted for the purpose of identifying technology improvements for an acquisition sensor for the detection of small objects in clear, sunlit cloud, fog, and mist conditions. Currently available mid-wave infrared (MWIR) and long-wave infrared (LWIR) technologies were studied. In addition, projected sensor technologies anticipated to be available in the near future, as well as idealized systems limited only by aperture size, integration time and instantaneous field of view (IFOV) were modeled. Both standard and polarimetric imaging sensors were included in the study. The Aero-Optical Prediction Tool (AerOPT) was used to model the performance of various sensors operating under the conditions of interest. Results indicate that LWIR systems may extend detection range in fog and mist environments and that polarimetry may reduce false alarm rate for sunlit cloud backgrounds. Importantly, polarimetric imaging does not appear to negatively impact detections.
IERUS Technologies investigated the feasibility of developing a high resolution, passive MWIR polarimetric imaging system for both day and night operation at short (1 – 5 meters) and long (1 – 2 km) range operation. The sensor system used a micro-polarizer array (MPA) over the focal plane array (FPA) in order to capture four channels of polarimetric information simultaneously. It also used an optical registration array (ORA) over the MPA in order to spatially register the polarimetric information. The MPA-ORA device is integral to the FPA, forming a drop-in-replacement, saving system size and weight relative to other polarimetric imaging technologies. A system was designed for a prototype that mitigates risk and demonstrates the utility of the ORA. The FPA employed is a MWIR array with a reticulated detector array which reduces electrical pixel-to-pixel crosstalk to zero. Polarization and radiometric performance predictions of the design will be presented.
Proc. SPIE. 10408, Laser Communication and Propagation through the Atmosphere and Oceans VI
KEYWORDS: Visibility through fog, Fiber optic gyroscopes, Scattering, Air contamination, Light scattering, Monte Carlo methods, Mie scattering, Atmospheric propagation, Atmospheric particles, Photon transport
Anyone who has driven through fog understands the detrimental effect scattering can have on your ability to see. When light interacts with a scattering center, in this case a fog droplet, it is scattered into a new direction, ultimately turning the world around you into a dull gray haze. In some fogs, visibility can be less than 100 meters. It would be possible to see through turbid media like fog if you can separate the scattered light from the unscattered, or ballistic, light; however, we must understand the light transport properties of the atmosphere to determine the optimum scheme. Here, we present an end-to-end simulation for polarized light transport through fog. Our approach can be summarized in three steps: compute the Mueller matrix for a single scattering interaction, ensemble average a distribution of sizes and shapes, and solve the light transport using a Monte Carlo simulation. For small spherical particles, such as fog, we use Mie theory to calculate the single scattering Mueller matrix, but this approach can be generalized to non-spherical particles using ray tracing for large particles or a T-matrix approach for smaller particles. Through this simulation, we are able to determine a backscattering Mueller matrix and a forward scattering Mueller matrix response function for the atmosphere as a function of position and detection angle.
IERUS Technologies, Inc. and the University of Alabama in Huntsville have partnered to perform characterization and development of algorithms and hardware for adaptive optics. To date the algorithm work has focused on implementation of the stochastic parallel gradient descent (SPGD) algorithm. SPGD is a metric-based approach in which a scalar metric is optimized by taking random perturbative steps for many actuators simultaneously. This approach scales to systems with a large number of actuators while maintaining bandwidth, while conventional methods are negatively impacted by the very large matrix multiplications that are required. The metric approach enables the use of higher speed sensors with fewer (or even a single) sensing element(s), enabling a higher control bandwidth. Furthermore, the SPGD algorithm is model-free, and thus is not strongly impacted by the presence of nonlinearities which degrade the performance of conventional phase reconstruction methods. Finally, for high energy laser applications, SPGD can be performed using the primary laser beam without the need for an additional beacon laser. The conventional SPGD algorithm was modified to use an adaptive gain to improve convergence while maintaining low steady state error. Results from laboratory experiments using phase plates as atmosphere surrogates will be presented, demonstrating areas in which the adaptive gain yields better performance and areas which require further investigation.
The Army has identified a need to rapidly identify, map, and classify natural and manmade features to aid situational
awareness as well as mission and tactical planning. To address these needs, Digital Fusion and Trex Enterprises have
designed a full Stokes, passive MMW imaging polarimeter that is capable of being deployed on an unmanned aerial
vehicle. Results of a detailed trade study are presented, where an architecture, waveband and target platform are
selected. The selected architecture is a pushbroom phased-array system, which allows the system to collect a wide fieldof-
view image with minimal components and weight. W band is chosen as a trade-off between spatial resolution,
weather penetration, and component availability. The trade study considers several unmanned aerial system (UAS)
platforms that are capable of low-level flight and that can support the MMW antenna. The utility of the passive Stokes
imager is demonstrated through W band phenomenology data collections at horizontal and vertical polarization using a
variety of natural and manmade materials. The concept design is detailed, along with hardware and procedures for both
radiometric and polarimetric calibration. Finally, a scaled version of the concept design is presented, which is being
fabricated for an upcoming demonstration on a small, manned aircraft.
Accurate calibration of polarimetric sensors is critical to reducing and analyzing phenomenology data, producing
uniform polarimetric imagery for deployable sensors, and ensuring predictable performance of polarimetric algorithms.
It is desirable to develop a standard calibration method, including verification reporting, in order to increase credibility
with customers and foster communication and understanding within the polarimetric community. This paper seeks to
facilitate discussions within the community on arriving at such standards.
Both the calibration and verification methods presented here are performed easily with common polarimetric equipment,
and are applicable to visible and infrared systems with either partial Stokes or full Stokes sensitivity. The calibration
procedure has been used on infrared and visible polarimetric imagers over a six year period, and resulting imagery has
been presented previously at conferences and workshops.
The proposed calibration method involves the familiar calculation of the polarimetric data reduction matrix by
measuring the polarimeter's response to a set of input Stokes vectors. With this method, however, linear combinations
of Stokes vectors are used to generate highly accurate input states. This allows the direct measurement of all system
effects, in contrast with fitting modeled calibration parameters to measured data. This direct measurement of the data
reduction matrix allows higher order effects that are difficult to model to be discovered and corrected for in calibration.
This paper begins with a detailed tutorial on the proposed calibration and verification reporting methods. Example
results are then presented for a LWIR rotating half-wave retarder polarimeter.
Imaging polarimetry is an emerging sensor technology that promises to improve the performance of sensor
systems when used as an adjunct to conventional intensity-based imaging. Several prototype systems capable of being
deployed from aircraft are under development. One system has successfully completed an airborne military utility
assessment and is being transitioned to operational status. As this technology continues to gain interest, it will become
necessary to both accurately predict the performance of proposed systems before they are fabricated as well as develop
modeling and simulation tools that will allow their performance to be evaluated for various operational scenarios. In
this paper we develop several performance prediction tools that can be used to address these needs; these models are
based on the micro-polarizer array (MPA) implementation of imaging polarimeters as this architecture is at the
forefront in the development of deployable systems.
Focal plane array (FPA) well size, polarizer extinction ratio (ER), pixel crosstalk, and processing algorithms
all play roles in the performance that can be attained by a proposed sensor. We discuss the polarimetric response of an
MPA-based polarimetric detector and use this model to illustrate the effects of these parameters on the sensor's
polarimetric performance, which we cast as noise equivalent degree of linear polarization (NeDoLP). Key conclusions
from these analyses are that the detector well size sets the upper limit on performance and that pixel crosstalk will
likely the biggest contributor to polarimetric loss in most systems.
Polarimetric imagery that is collected from time-sequential and multiple image format sensors all have potential for image misregistration. Since polarization is usually measured as small differences between radiometric measurements, it is highly sensitive to misregistration, especially at regions of high contrast. The general consensus in the polarization community is that image misregistration on the order of 1/10th of a pixel can introduce artifacts in polarization images. If the registration is not achieved and maintained to this resolution, the data must be registered in software. Typically, rotation and translation (horizontal and vertical) are the main transformations that need to be corrected. It is desirable to have a registration algorithm that determines rotations and translations to 1/10th of a pixel, does not require user intervention, takes minimal computation time, and is based on analytical (non-iterative), automated calculations. This paper details an analytical, automated registration algorithm that corrects for rotation and translations by using a Fourier transform technique. Examples of images registered with this algorithm, and estimates of residual misregistrations are presented. Typical processing times are also given.