Realistic backgrounds are necessary to support high fidelity hardware-in-the-loop testing. Advanced avionics and weapon system sensors are driving the requirement for higher resolution imagery. The model-test-model philosophy being promoted by the T&E community is resulting in the need for backgrounds that are realistic or virtual representations of actual test areas. Combined, these requirements led to a major upgrade of the terrain database used for hardware-in-the-loop testing at the Guided Weapons Evaluation Facility (GWEF) at Eglin Air Force Base, Florida. This paper will describe the process used to generate the high-resolution (1-foot) database of ten sites totaling over 20 square kilometers of the Eglin range. this process involved generating digital elevation maps from stereo aerial imagery and classifying ground cover material using the spectral content. These databases were then optimized for real-time operation at 90 Hz.
Clutter metrics are important image measures for evaluating the expected performance of sensors and detection algorithms. Typically, clutter metrics attempt to measure the degree to which background objects resemble targets. That is, the more target-like objects or attributes in the background the higher the clutter level. However, it is critically important that the characteristics of the sensor systems and the detection algorithms be included in any measure of clutter. For example, clutter to a coarse resolution sensor coupled with a pulse thresholding detection algorithm is not necessarily clutter to a second generation FLIR with a man in the loop. Using present state- of-the-art first and second order clutter metrics and respective performance studies, a new class of sensor/algorithm clutter metrics will be derived which explicitly use characteristics of the sensor and detection algorithms. A methodology will be presented for deriving sensor/algorithm dependent clutter metric coefficients and algorithms for a broad class of systems.
This paper describes a methodology which has been successfully used to create high fidelity three-dimensional infrared (IR) signature models of terrain backgrounds for use in digital simulations by the U.S. Army Missile Command. Topics discussed include (1) derivation of database fidelity and resolution requirements based upon system parameters, (2) use of existing digital elevation maps (DEMs) (3) generation of digital elevation maps from stereo aerial and satellite imagery, and (4) classification of ground cover materials.
A psychovisual experiment with 80 observers determined the amount of additive noise an observer could tolerate in resolving 36 different bar targets. The results show that the detection threshold noise can be represented by a simple analytical expression with contrast and spatial frequency as variables. The expression that closely matched the data is Vnoise (6.4C + 0.68)/v' , where Vnoise IS the amount of noise that can be tolerated, C is the contrast, and is the spatial frequency in cycles! radian. The numerical values are a function of the monitor used and are readily obtained by a simple measurement.
Conference Committee Involvement (4)
Targets and Backgrounds XII: Characterization and Representation
17 April 2006 | Orlando (Kissimmee), Florida, United States
Targets and Backgrounds XI: Characterization and Representation
28 March 2005 | Orlando, Florida, United States
Targets and Backgrounds X: Characterization and Representation
12 April 2004 | Orlando, Florida, United States
Targets and Backgrounds IX: Characterization and Representation