KEYWORDS: Imaging systems, Sensors, Signal to noise ratio, Performance modeling, Target detection, Signal attenuation, Contrast transfer function, Atmospheric modeling, Extremely high frequency, Backscatter
The U.S. Army Research Laboratory (ARL) has continued to develop and enhance a millimeter-wave (MMW) and submillimeter- wave (SMMW)/terahertz (THz)-band imaging system performance prediction and analysis tool for both the detection and identification of concealed weaponry, and for pilotage obstacle avoidance. The details of the MATLAB-based model which accounts for the effects of all critical sensor and display components, for the effects of atmospheric attenuation, concealment material attenuation, and active illumination, were reported on at the 2005 SPIE Europe Security and Defence Symposium (Brugge). An advanced version of the base model that accounts for both the dramatic impact that target and background orientation can have on target observability as related to specular and Lambertian reflections captured by an active-illumination-based imaging system, and for the impact of target and background thermal emission, was reported on at the 2007 SPIE Defense and Security Symposium (Orlando). Further development of this tool that includes a MODTRAN-based atmospheric attenuation calculator and advanced system architecture configuration inputs that allow for straightforward performance analysis of active or passive systems based on scanning (single- or line-array detector element(s)) or staring (focal-plane-array detector elements) imaging architectures was reported on at the 2011 SPIE Europe Security and Defence Symposium (Prague). This paper provides a comprehensive review of a newly enhanced MMW and SMMW/THz imaging system analysis and design tool that now includes an improved noise sub-model for more accurate and reliable performance predictions, the capability to account for postcapture image contrast enhancement, and the capability to account for concealment material backscatter with active-illumination- based systems. Present plans for additional expansion of the model’s predictive capabilities are also outlined.
The U.S. Army Research Laboratory (ARL) and the U.S. Army Night Vision and Electronic Sensors Directorate
(NVESD) have developed a terahertz-band imaging system performance model/tool for detection and identification of
concealed weaponry. The details of the MATLAB-based model which accounts for the effects of all critical sensor and
display components, and for the effects of atmospheric attenuation, concealment material attenuation, and active
illumination, were reported on at the 2005 SPIE Europe Security & Defence Symposium (Brugge). An advanced
version of the base model that accounts for both the dramatic impact that target and background orientation can have on
target observability as related to specular and Lambertian reflections captured by an active-illumination-based imaging
system, and for the impact of target and background thermal emission, was reported on at the 2007 SPIE Defense and
Security Symposium (Orlando). This paper will provide a comprehensive review of an enhanced, user-friendly,
Windows-executable, terahertz-band imaging system performance analysis and design tool that now includes additional
features such as a MODTRAN-based atmospheric attenuation calculator and advanced system architecture
configuration inputs that allow for straightforward performance analysis of active or passive systems based on scanning
(single- or line-array detector element(s)) or staring (focal-plane-array detector elements) imaging architectures. This
newly enhanced THz imaging system design tool is an extension of the advanced THz imaging system performance
model that was developed under the Defense Advanced Research Project Agency's (DARPA) Terahertz Imaging
Focal-Plane Technology (TIFT) program. This paper will also provide example system component (active-illumination
source and detector) trade-study analyses using the new features of this user-friendly THz imaging system performance
analysis and design tool.
The Federal Aviation Administration (FAA) is presently engaged in research to quantify the visibility of aircraft under
two important scenarios: aircraft observed directly by human operators in air traffic control towers (ATCT's), and
aircraft observed by human operators through unmanned aerial vehicle (UAV) sensors viewed through ground-based
display systems. Previously, an ATCT visibility analysis software tool (FAA Vis) was developed by the U.S. Army
Research Laboratory (ARL) in collaboration with the U.S. Army's Night Vision and Electronic Sensors Directorate
(NVESD) and the FAA. This tool predicts the probability of detection, recognition, and identification of various aircraft
by human observers as a function of range and ATCT height. More recently, a baseline version of a UAV See-And-
Avoid visibility analysis software tool was also developed by ARL, again in collaboration with NVESD and the FAA.
Important to the calibration of these tools is the empirical determination of target discrimination difficulty criteria.
Consequently, a set of human perception experiments were designed and conducted to empirically determine the target
recognition and identification discrimination difficulty criteria for a representative set of aircraft. This paper will report
on the results and analyses of those experiments.
Real MWIR Persistent Surveillance (PS) data was taken with a single human walking from a known point to different tents in the PS sensor field of view. The spatial resolution (ground sample distance) and revisit rate was varied from 0.5 to 2 meters and 1/8th to 4 Hz, respectively. A perception experiment was conducted where the observer was tasked to track the human to the terminal (end of route) tent. The probability of track is provided as a function of ground sample distance and revisit rate. These results can help determine PS design requirements for tracking and back-tracking humans on the ground. This paper begins with a summary of two previous simulation experiments: one for human tracking and one for vehicle tracking.
The U.S. Army Night Vision and Electronic Sensors Directorate (NVESD) and the U.S. Army Research Laboratory
(ARL) have developed a terahertz-band imaging system performance model for detection and identification of
concealed weaponry. The details of this MATLAB-based model which accounts for the effects of all critical sensor and
display components, and for the effects of atmospheric attenuation, concealment material attenuation, and active
illumination, were reported on at the 2005 SPIE Europe Security and Defence Symposium. The focus of this paper is to
report on recent advances to the base model which have been designed to more realistically account for the dramatic
impact that target and background orientation can have on target observability as related to specular and Lambertian
reflections captured by an active-illumination-based imaging system. The advanced terahertz-band imaging system
performance model now also accounts for target and background thermal emission, and has been recast into a user-friendly,
Windows-executable tool. This advanced THz model has been developed in support of the Defense Advanced
Research Project Agency's (DARPA) Terahertz Imaging Focal-Plane Technology (TIFT) program. This paper will
describe the advanced THz model and its new radiometric sub-model in detail, and provide modeling and experimental
results on target observability as a function of target and background orientation.
This paper describes the design and performance of the U.S. Army RDECOM CERDEC Night Vision and Electronic
Sensors Directorate's (NVESD), active 0.640-THz imaging testbed, developed in support of the Defense Advanced
Research Project Agency's (DARPA) Terahertz Imaging Focal-Plane Technology (TIFT) program. The laboratory
measurements and standoff images were acquired during the development of a NVESD and Army Research Laboratory
terahertz imaging performance model. The imaging testbed is based on a 12-inch-diameter Off-Axis Elliptical (OAE)
mirror designed with one focal length at 1 m and the other at 10 m. This paper will describe the design considerations of
the OAE-mirror, dual-capability, active imaging testbed, as well as measurement/imaging results used to further develop
the model.
The dynamic range of the signal return from metals is a significant source of image interpretation difficulty. Techniques such as logarithmic image compression have been used to improve the recognition. Alternative techniques for improvement may be developed. This development depends in part on the ability to accurately model the surface reflective behavior including phase shifts introduced by the reflection. This work presents the results of an enhanced model development. Models of high frequency behavior in materials divide into regions such as non-relaxation region, relaxation region, optical absorption and plasma frequencies. In traditional infrared and longer wavelength imaging systems, optical absorption may play a role and it is generally assumed that the system operates in or very near the relaxation region defined as frequencies significantly greater than the reciprocal of the Boltzmann relaxation time. Though typical THz frequencies are below the relaxation time, they are not far enough below to be considered completely in the non-relaxation region. This introduces a number of issues atypical of imaging in either the RF or IR regime. Further realism is gained from the incorporation of plastic into the reflectivity and emissivity model. Empirical model validation is accomplished for selected materials.
Terahertz imaging sensors are being considered for providing a concealed weapon identification capability for military and security applications. In this paper the difficulty of this task is assessed in a systematic way. Using imaging systems operating at 640 GHz, high resolution imagery of possible concealed weapons has been collected. Information in this imagery is removed in a controlled and systematic way and then used in a human observer perception experiment. From the perception data, a calibration factor describing the overall difficulty of this task was derived. This calibration factor is used with a general model of human observer performance developed at the US Army Night Vision and Electronic Sensors Directorate to predict the task performance of observers using terahertz imaging sensors. Example performance calculations for a representative imaging sensor are shown.
We have developed several millimeter/submillimeter/terahertz systems to study active and passive imaging and associated phenomenology. For measuring the transmission and scattering properties of materials, we have developed a dual rotary stage scattering system with active illumination and a Fourier Transform spectrometer. For imaging studies, we have developed a system based on a 12-inch diameter raster-scanned mirror. By interchange of active sources and both heterodyne and bolometric detectors, this system can be used in a variety of active and passive configurations. The laboratory measurements are used as inputs for, and model calibration and validation of, a terahertz imaging system performance model used to evaluate different imaging modalities for concealed weapon identification. In this paper, we will present examples of transmission and scattering measurements for common clothing as well as active imaging results that used a 640 GHz source and receiver.
The U.S. Army Night Vision and Electronic Sensors Directorate and the U.S. Army Research Laboratory have developed a terahertz-band imaging system performance model for detection and identification of concealed weaponry. The MATLAB-based model accounts for the effects of all critical sensor and display components, and for the effects of atmospheric attenuation, concealment material attenuation, and active illumination. The model is based on recent U.S. Army NVESD sensor performance models that couple system design parameters to observer-sensor field performance using the acquire methodology for weapon identification performance predictions. This THz model has been developed in support of the Defense Advanced Research Project Agencies' Terahertz Imaging Focal-Plane-Array Technology (TIFT) program and is presently being used to guide the design and development of a 0.650 THz active/passive imaging system. This paper will describe the THz model in detail, provide and discuss initial modeling results for a prototype THz imaging system, and outline plans to validate and calibrate the model through human perception testing.
Enhancement of undersampled imager performance has been demonstrated using superresolution techniques. In these techniques, the optical flow of the scene or the relative subpixel shifts among various snapshots of the scene are calculated, and a high-resolution grid is populated with spatial data using various algorithms. Performance enhancement has been demonstrated for the case of a static image with the undersampled imager compared with a static image that has been acquired through a frame series in a dynamic scene. In this research, the performance is compared for four cases: static image with undersampled imager, static image with superresolution frame sequence, dynamic image with undersampled imager, and dynamic image with superresolution frame sequence.
The enhancement of undersampled imager performance has been demonstrated using super-resolution techniques. In these techniques, the optical flow of the scene or the relative sub-pixel shifts between frames is calculated and a high resolution grid is populated with spatial data based as a result of scene motion. Performance enhancement has been demonstrated for the case of a static image with the undersampled imager output compared to a static image that has been acquired through a frame series in a dynamic scene. In this research, the performance is compared for four cases: static image with undersampled imager, static image with super-resolution frame sequence, dynamic image with undersampled imager, and dynamic image with super-resolution frame sequence.
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