Comparison of reflective band (Vis, NIR, SWIR, eSWIR) performance in daytime reduced illumination conditions.

Daytime low-light conditions such as overcast, dawn, and dusk pose a challenge for object discrimination in the reflective bands, where the majority of illumination comes from reflected solar light. In reduced-illumination conditions, the sensor signal-to-noise ratio can suffer, inhibiting range performance for detecting, recognizing, and identifying objects of interest. This performance reduction is more apparent in the longer wavelengths where there is less solar light. Range performance models show a strong dependence on cloud type and thickness, as well as time of day across the reflective wavebands. Through an experimental and theoretical analysis of a passive sensitivity- and resolution-matched testbed, we compare Vis (0.4-0.7 µm), NIR (0.7-1 µm), SWIR (1-1.7 µm), and eSWIR (2-2.5 µm) to assess the limiting cases in which reduced illumination inhibits range performance. The time during dawn and dusk is brief yet does show significant range performance reduction for SWIR and eSWIR. Under heavy cloud cover, eSWIR suffers the most at range due to a low signal-to-noise ratio. In cases of severe reduction in illumination, we propose utilizing active illumination or the emissive component of eSWIR to improve the signal-to-noise ratio for various discrimination tasks.

Radiometry and contrast-to-noise ratio for continuous-wave and laser range-gated active imaging systems.

Resolution and sensitivity must be considered in the design of an active imaging system. System sensitivity is characterized by the signal-to-noise or contrast-to-noise ratio and is derived through radiometry. We present a tutorial for the radiometry associated with the contrast-to-noise ratio for active continuous-wave and laser range-gated imaging systems, giving a useful metric for determining reflective-band sensor performance against a target and background. A calculation of the full power and contrast-to-noise ratio terms is shown for an example case, and all relevant radiometric signal terms are covered while describing the assumptions made. Coherent effects on signal-to-noise ratio are excluded from this analysis.

Mid-wave and long-wave infrared signature model and measurement of power lines against atmospheric path radiance.

The signal to noise ratio and corresponding visibility of power cables as seen by military aircrafts is critical for crew safety. During low altitude operations, rotorcraft systems must be able to navigate these power lines during flight. Many of these military missions are flown at night which means the reflective bands including the visible, near infrared and short-wave infrared do not provide sufficient light. However, the emissive bands of the mid-wave infrared (MWIR) and long-wave infrared (LWIR) can be used to distinguish the location of these wires. LWIR sensors are typically used for pilotage applications. In both the LWIR and MWIR, the signal to noise depends on the wire emissivity and reflectivity as well as the ground and sky background path radiance. The signal to noise ratio is strongly dependent on the elevation of the viewing angle. In this paper, we model the signal to noise ratio as a function of elevation viewing angle using wire reflectivity and emissivity as well as MODTRAN calculations for path radiance. We also take MWIR and LWIR measurements to compare these two bands to the modelling results. We provide a summary of both model and measurements and make conclusions.

Detection of small targets in the infrared: an infrared search and track tutorial.

Airborne target detection in the infrared has been classically known as infrared search and track or IRST. From a military point of view, it can be described as target detection at long ranges where the target image is subpixel in size. Here, the target is "unresolved." It can also describe the detection of aircraft near the observer using distributed apertures in a spherical detection field. From a commercial point of view, an important application is drone detection near live airport operations. As drones become more common, the dual-use functionality of IRST systems is expanding. Technology improvements for IRST systems include the wide proliferation of infrared staring focal planes. New readout integrated circuits allow for time-delay-integration of large format detectors. Stare-step sensors in the future appear to be as common as gimbal-scanned thermal imagers. Detection probability analysis and IRST sensor design is different than targeting system design. We provide a tutorial here on IRST system calculations as well as discussions on broadband versus spectral calculations and new technology considerations.

Detection of Burmese pythons in the near-infrared versus visible band.

Human task performance studies are commonly used for detecting and identifying potential military threats. In this work, these principles are applied to detection of an environmental threat: the invasive Burmese python. A qualitative detection of Burmese pythons with a visible light camera and an 850 nm near-infrared (NIR) camera was performed in natural Florida backgrounds. The results showed that the difference in reflectivity between the pythons and native foliage was much greater in NIR, effectively circumventing the python's natural camouflage in the visible band. In this work, a comparison of detection performance in the selected near-infrared band versus the visible band was conducted. Images of foliage backgrounds with and without a python were taken in each band in daylight and at night with illumination. Intensities of these images were then calibrated and prepared for a human perception test. Participants were tasked with detecting pythons, and the human perception data was used to compare performance between the bands. The results show that the enhanced contrast in the NIR enabled participants to detect pythons at 20% longer ranges than the use of visible imagery.

Design considerations for advanced MWIR target acquisition systems.

In this paper, mid-wave infrared (MWIR) sensor optimization is provided as a function of the parameter Fλ/d, where F is the f-number, λ is the effective wavelength, and d is the detector pitch. For diffraction limited systems, acquisition range is related to the instantaneous field of view (detector limited operation) when Fλ/d<1, and to the optical properties (optics limited operation) when Fλ/d>2.0. Range performance is a combination of detector and optics resolution limits when Fλ/d is in between. When the system is not strictly diffraction or sampling limited, the optimal Fλ/d depends on other system component characteristics and conditions. Optical system aberrations affect system resolution and decrease range performance. As background shot noise, dark current shot noise, and read noise increase, range decreases. In the infrared spectral region, atmospheric absorption leads to reemission of thermal energy. The detected reemission creates additional shot noise. Atmospheric attenuation greatly affects MWIR sensor range performance. Next-generation MWIR sensors will have smaller detectors, larger arrays, and better sensitivity to enable Fλ/d-based optimization. Previous studies (ΔT=4K for tracked vehicles) suggest that an initial design point is Fλ/d≈2.0. When detecting low contrast targets (ΔT∼0.1K), sensor gain is used to increase the signal for a desired displayed contrast. This gain increases displayed noise and reduces acquisition range. This is typically not an issue for long-wave infrared sensors due to the excess number of photons in the 8-12 µm band but poses a problem for MWIR sensors, which are photon starved. Under such scenarios, the optimum Fλ/d appears to be about 1.5 for MWIR sensors. The results here provide reasonable strategies for MWIR system optimization and a direction associated with future MWIR focal plane development.

Performance comparison of sparse array millimeter wave imager configurations.

Millimeter wave imaging systems are a promising candidate for several applications such as indoor security, industrial non-destructive evaluation, and automotive radar systems. In this paper, we compare the performance of various array configurations that can be enabled by recent automotive radar chips, for imaging applications. High resolution real-time imaging requires an extensive number of measurements which demands a large number of emitters and receivers. Hence, cost and size become major considerations in the design process. In an attempt to reduce the number of emitter and receiver elements, we compare various antenna array architectures to optimize the hardware implementation for high resolution imaging. We consider mono-static single-input-single-output (SISO), multi-static multiple-input-multiple-output (Full-MIMO), and hybrid localized MIMO-SISO (Local-MIMO) architectures. The computationally reconstructed image quality and point spread function from each architecture are compared and traded for the system engineering complexity and cost. We present measurement results from a Synthetic Aperture Radar (SAR) system based on an automotive radar sensor to ensure it is representative of the system's physics. The comparative results of the SISO, Full-MIMO and Local-MIMO simulations provide for affordable alternatives to the high cost SISO approach.

Burmese python target reflectivity compared to natural Florida foliage background reflectivity.

The Florida Everglades is infested with Burmese pythons caused by the release of exotic pets in the 1980s. The current estimates are between 30,000 and 300,000 pythons, where the result is a severe decline in Everglade mammals: 90% reductions in raccoon, opossum, bobcats, and foxes. The marsh rabbits are completely gone. The population of the pythons is rapidly increasing exponentially with 20-50 eggs per snake with a life span of up to 20 years. Pythons have been captured in the Everglades with lengths of nearly 6 m. Researchers in the state of Florida are concerned that these pythons are (1) permanently damaging the Everglades, (2) migrating further north into populated areas of Florida, and (3) endangering wildlife, pets, and eventually, people. There have been a number of sensing efforts attempted in the large-area detection of pythons, where limited success has been achieved. For example, infrared sensors have been applied to the problem, but the pythons are cold-blooded, so the infrared bands do not work well. Imec has leveraged its expertise and infrastructure in semiconductor processing to produce highly compact, higher performance, and relatively cheaper hyperspectral image sensors and camera systems. In this work, Imec teamed with the University of Florida and Extended Reality Systems to obtain hyperspectral reflectivity measurements of Burmese pythons along with natural Florida background foliage to determine bands or band combinations that may be exploited in the large-area detection of pythons. The bands investigated are the visible-near infrared (or VisNIR) and the shortwave infrared (SWIR) bands. The results show that there are enough differences in the data collection such that a single band, inexpensive VisNIR band camera may provide reasonable results and a two-band, VisNIR/SWIR combination may provide higher performance results. In this paper, we provide the VisNIR results.

Echelle crossed grating millimeter wave beam scanner.

We present a two-dimensional, active, millimeter-wave, electronic beam scanner, with Doppler capabilities for stand-off imaging. The two-dimensional scan is achieved by mapping the millimeter wave spectrum to space using a pair of crossed gratings. The active transceiver and heterodyne quadrature detection allow the measurement of the relative phase between two consecutive measurements and the synthesis of the scene's Doppler signature. The frame rate of the imager is currently limited by the sweep rate of the vector network analyzer which is used to drive the millimeter wave extenders. All of the beam steering components are passive and can be designed to operate at any wavelength. The system design, characterization and measurements are presented and further uses and improvements are suggested.

Target identification and navigation performance modeling of a passive millimeter wave imager.

Human task performance using a passive interferometric millimeter wave imaging sensor is modeled using a task performance modeling approach developed by the U.S. Army Night Vision and Electronic Sensors Directorate. The techniques used are illustrated for an imaging system composed of an interferometric antenna array, optical upconversion, and image formation using a shortwave infrared focal plane array. Two tasks, target identification and pilotage, are modeled. The effects of sparse antenna arrays on task performance are considered. Applications of this model include system trade studies for concealed weapon identification, navigation in fog, and brownout conditions.