The Effects of Certain Gimbal Orders on Target Acquisition and Workload

1975 ◽  
Vol 17 (6) ◽  
pp. 571-576 ◽  
Author(s):  
Dennis L. Price
Keyword(s):  
Target Detection ◽  
Target Acquisition ◽  
Identification Performance ◽  
Imaging Sensors ◽  
Operator Workload

If air-to-ground imaging sensors are mounted to aircraft by different gimbal order systems, the displayed scene will rotate differently, even though the flight paths are identical. Eighteen experienced pilots were tested to investigate the effects of three gimbal orders (roll-pitch, yaw-pitch, and pitch-yaw) on target detection, recognition, and identification performance, and also on operator workload. The pitch-yaw gimbal order was associated with the greatest range-to-target scores and the lightest workloads.

The Effects of Certain Gimbal Orders and Workloads on Target Acquisition

1974 ◽  
Vol 18 (2) ◽  
pp. 153-157
Author(s):  
Dennis L. Price
Keyword(s):  
Target Detection ◽  
Identification Performance ◽  
Target Task ◽  
Terrain Model ◽  
Spare Time ◽  
Word Task ◽  
Heavy Workload ◽  
Improved Performance ◽  
Imaging Sensors ◽  
Operator Workload

If air-to-ground imaging sensors are mounted to aircraft by different gimbal order systems, the scenery at the displays will rotate differently, even though the flight paths are identical. Eighteen experienced pilots were tested to investigate the effects such scene motions might have on target detection, recognition, and identification performance, and also on operator workload. The Martin Marietta 600:1 scale terrain model was used to provide the imagery of three gimbal orders: roll-pitch, yaw-pitch, and pitch-yaw. Target runs simulated started at 20k ft. slant range, and maintained a 4k ft. altitude, and 2500 or 5000 feet offset. They were 30-second runs at a speed of 350 knots. The pitch-yaw gimbal order was associated with the greatest range-to-target scores and the lightest workloads. Also, the workload measured for each gimbal order and the workload measured for a word task from the Montana Meaningfulness Scale were added together for each subject. The sum was the estimated workload for that subject for the combined tasks, which were presented on two monitors. The six subjects with the heaviest workload estimates and the six with the lightest were compared on range-to-target scores. The heavy workload group demonstrated a trend effect for improved performance compared to the light workload group, p < .01. However, significant degraded performance occurred when the results of all subjects for this words and target task were compared with similar trials in which the second display was monitored during the observer's spare time only.

Target Acquisition in Realistic Terrain

1977 ◽  
Vol 21 (3) ◽  
pp. 249-253 ◽  
Author(s):  
Lawrence A. Scanlan
Keyword(s):  
Mathematical Models ◽  
Target Detection ◽  
Optical Sensor ◽  
Component Model ◽  
Target Acquisition ◽  
Target Search ◽  
Average Luminance ◽  
Two Component ◽  
Uniform Background ◽  
Detection And Recognition

A number of mathematical models of target acquisition have been developed to predict the performance of electro-optical sensor systems. None of these models, however, adequately treat the influence of the background scene on operator tactical target detection and recognition. Most assume a uniform background of some average luminance: a situation that is unlikely to occur in any realistic mission. The failure to include the influence of backgrounds of varying complexity may result in erroneous predictions of performance that are highly optimistic. The reported research was directed toward the issues of background scene complexity. The data are interpreted as evidence for a two-component model of target search and detection.

Target Detection and Identification Performance Using an Automatic Target Detection System

2016 ◽  
Vol 59 (2) ◽  
pp. 242-258 ◽  
Author(s):  
Adam J. Reiner ◽  
Justin G. Hollands ◽  
Greg A. Jamieson
Keyword(s):  
Target Detection ◽  
Task Difficulty ◽  
Detection System ◽  
Decision Criterion ◽  
Identification Performance ◽  
Automatic Target Detection ◽  
Immersive Virtual Environment ◽  
Detection And Identification ◽  
Scene Illumination ◽  
Night Illumination

Objective: We investigated the effects of automatic target detection (ATD) on the detection and identification performance of soldiers. Background: Prior studies have shown that highlighting targets can aid their detection. We provided soldiers with ATD that was more likely to detect one target identity than another, potentially acting as an implicit identification aid. Method: Twenty-eight soldiers detected and identified simulated human targets in an immersive virtual environment with and without ATD. Task difficulty was manipulated by varying scene illumination (day, night). The ATD identification bias was also manipulated (hostile bias, no bias, and friendly bias). We used signal detection measures to treat the identification results. Results: ATD presence improved detection performance, especially under high task difficulty (night illumination). Identification sensitivity was greater for cued than uncued targets. The identification decision criterion for cued targets varied with the ATD identification bias but showed a “sluggish beta” effect. Conclusion: ATD helps soldiers detect and identify targets. The effects of biased ATD on identification should be considered with respect to the operational context. Application: Less-than-perfectly-reliable ATD is a useful detection aid for dismounted soldiers. Disclosure of known ATD identification bias to the operator may aid the identification process.

Accommodation and the Acquisition of Distant Targets by Observers with Superior Vision

1983 ◽  
Vol 27 (3) ◽  
pp. 259-263
Author(s):  
Kirk Moffitt
Keyword(s):  
Target Detection ◽  
Target Acquisition ◽  
Distance Information ◽  
Acquisition Performance ◽  
On Demand ◽  
Series Of Experiments ◽  
Visual Accommodation ◽  
Small Targets ◽  
Dark Focus ◽  
Military Pilots

The visual accommodation ability of young observers with healthy eyeballs has typically been underestimated. A series of experiments and demonstrations was conducted to study how a pilot might use his eyes to optimize target acquisition performance in different visual environments. Observers with uncorrected far acuities of 20/20 or better were selected for participation. Target acquisition tasks were performed while accommodation was simultaneously monitored with an infrared optometer. The target was always small and located at optical infinity. The average dark focus was more distant than is typically reported and tended to shift outwards with experience on the optometer. When observers were provided with distance information, half were apparently able to “look through” near peripheral texture in order to optimize accommodation accuracy and target detection performance. Although most observers were capable of using imagery to shift their accommodation outwards in the dark, this did not predict the ability to “look through” near texture. In a subsequent demonstration, two observers were able to focus and defocus small targets on demand. Implications for military pilots, many of whom have superior vision, are discussed.

Background Influence on Visual Accommodation: Implications for Target Acquisition

1981 ◽  
Vol 25 (1) ◽  
pp. 277-281 ◽  
Author(s):  
Russell A. Benel ◽  
Denise C. R. Benel
Keyword(s):  
Target Detection ◽  
High Contrast ◽  
Target Acquisition ◽  
Visual Accommodation

The accommodation of two groups of six observers each of whom viewed high-contrast checkerboard targets presented at six distances (0.9, 1.8, 3.7, 7.3, 16.6 and 29.3m) against either of two backgrounds (highly textured or textureless) was measured with a laser optometer. Significant differences existed between the accommodative responses at each distance due to backgrounds. Implications for size-distances perception and target detection are discussed.

Sensor performance conversions for infrared target acquisition and intelligence–surveillance–reconnaissance imaging sensors

1999 ◽  
Vol 38 (28) ◽  
pp. 5936 ◽  
Author(s):  
Ronald G. Driggers ◽  
Mel Kruer ◽  
Dean Scribner ◽  
Penny Warren ◽  
Jon Leachtenauer
Keyword(s):  
Target Acquisition ◽  
Sensor Performance ◽  
Imaging Sensors
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