To investigate the benefits of multiband infrared sensor design for target detection, search and detection experiments were conducted in the midwave infrared (MWIR) and longwave infrared (LWIR) wavebands in both rural and urban battlefields. In each battlefield environment, real imagery was collected in both bands by a single sensor using the same optics for both bands, resulting in perfect co-registration of the imagery. In order to study the performance impact of the spectral content, and not diffraction or other sensor-specific differences, the images were processed as needed so that differences in resolution due to diffraction were mitigated. The results of perception experiments, including detection probabilities, search times, and false alarm data, were compared between the wavebands.
The U.S. Army's Night Vision and Electronic Sensors Directorate (NVESD) Modeling and Simulation
Division is responsible for developing and enhancing electro-optic/infrared sensor performance models
that are used in wargames and for sensor trade studies. Predicting how well a sensor performs a military
task depends on both the physics of the sensor and how well observers perform specific tasks while using
that sensor. An example of such a task could be to search and detect targets of military interest. Another
task could be to identify a target as a threat or non-threat. A typical sensor development program
involves analyses and trade-offs among a number of variables such as field of view, resolution, range,
compression techniques, etc. Observer performance results, obtained in the NVESD perception lab,
provide essential information to bridge the gap between the physics of a system and the humans using that
system. This information is then used to develop and validate models, to conduct design trade-off studies
and to generate insights into the development of new systems for soldiers in surveillance, urban combat,
and all types of military activities. Computer scientists and engineers in the perception lab design tests
and process both real and simulated imagery in order to isolate the effect or design being studied. Then,
in accordance with an approved protocol for human subjects research, experiments are administered to the
desired number of observers. Results are tabulated and analyzed. The primary focus of this paper is to
describe current capabilities of the NVESD perception lab regarding computer-based observer
performance testing of sensor imagery, what types of experiments have been completed and plans for the
Flash laser detection and ranging (LADAR) systems are increasingly used in robotics applications
for autonomous navigation and obstacle avoidance. Their compact size, high frame rate, wide field
of view, and low cost are key advantages over traditional scanning LADAR devices. However,
these benefits are achieved at the cost of spatial resolution. Super-resolution enhancement can be
applied to improve the resolution of flash LADAR devices, making them ideal for small robotics
applications. Previous work by Rosenbush et al. applied the super-resolution algorithm of
Vandewalle et al. to flash LADAR data, and observed quantitative improvement in image quality in
terms of number of edges detected. This study uses the super-resolution algorithm of Young et al. to
enhance the resolution of range data acquired with a SwissRanger SR-3000 flash LADAR camera.
To improve the accuracy of sub-pixel shift estimation, a wavelet preprocessing stage was developed
and applied to flash LADAR imagery. The authors used the triangle orientation discrimination
(TOD) methodology for a subjective evaluation of the performance improvement (measured in terms
of probability of target discrimination and subject response times) achieved with super-resolution.
Super-resolution of flash LADAR imagery resulted in superior probabilities of target discrimination
at the all investigated ranges while reducing subject response times.
Perception experiments were conducted at Night Vision and Electronic Sensors Directorate (NVESD) to investigate the effect of targets in defilade on the search task. Vehicles were placed in a simulated terrain and were either fully exposed, partially exposed, or placed in hull defilade. These images, along with a number of no-target images, were presented in a time-limited search perception experiment using military observers. The results were analyzed and compared with ACQUIRE predictions to determine if there are factors, other than size, affecting the search task when targets are in defilade.
Recent work by the US Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate (NVESD) has led to the Time-Limited Search (TLS) model, which has given new formulations for the field of view (FOV) search times. The next step in the evaluation of the overall search model (ACQUIRE) is to apply these parameters to the field of regard (FOR) model. Human perception experiments were conducted using synthetic imagery developed at NVESD. The experiments were competitive player-on-player search tests with the intention of imposing realistic time constraints on the observers. FOR detection probabilities, search times, and false alarm data are analyzed and compared to predictions using both the TLS model and ACQUIRE.