Border Surveilance, Tower Camera, Vehicle Thermal imager, Day Night IR Long Range camera, 1km 2km 3km 4km 5km 10km 15km 20km IR thermal 200mm 300mm

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Range, Resolution and FOV of EV3000-D-IR uncooled Thermal

Thermal Imager 320x240 with 19mm, 25mm, 50mm, or 100mm lens

Day Camera with Fog Filter with 300mm, 550/1100mm, 660/1680 and 825mm optical zoom lenses

 

 

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EV3000-D-IR Thermal Camera

IR Camera specification
Camera Model EV3000-D-IR50 EV3000-D-IR100
Pixel pitch (µm)
H (µm)
 
V (µm)
Number of Pixels
H-pixels
 
V-pixels
Detector Size (mm)
H-size
 
V-size
9.60
7.20
 
Field of View
Lens focal length mm

Enter 50 for EV3000-D-IR50

Enter 100 for EV3000-D-IR100 default

Field of View (FOV) (degrees) °
H-FOV
 
V-FOV
 
D-FOV
1.10
 
0.82
 
1.37
Pixel Field of View (IFOV) (mrad)
H-FOV
 
V-FOV
0.02
 
0.02
 
Calculate Field Of View at specific Range
Range to object meters Enter range and click here
Field of View at Range (meters)
H-IFOV
 
V-IFOV
96.00
 
72.00

This represent target size at Range to be in 100% of Monitor

Example if we have target 96x72 meters it will fill monitor at 5 km range

Pixel Field of View at Range (cm)
H-IFOV
 
V-IFOV
15.00
 
15.00
 
Range
H-Size of object meters Enter target size and click here
Max Detection Range (4 pixels)
% of display
Range (meters)
 
% of H display
7500.00
 
0.62%
 
Max Recognition Range (16 pixels)
% of display
Range (meters)
 
% of H display
1875.00
 
2.50%
Max Identification Range(26 pixels)% of display
Range (meters)
 
% of H display
1153.84
 
5.00%
 
Description and Historical Information
 
This Calculator enables the user to easily estimate the maximum range from which an object can be detected when using various infrared camera platforms. It is important to note that these estimates assume that range performance is based solely on image quality yielding a method of estimation that's simple to implement. The estimates are based solely on the object size, distance, camera objective lens and camera detector parameters. Object temperature, emissivity, atmospheric conditions, reflectivity and other factors are not considered. In this regard, the object size and focal length of the objective lens are variables to be entered by the user. The spreadsheet also provides information as to the angular and spatial field-of-view of different camera systems at a specified range.
 
The calculations used here are based on the "Johnson Criteria" which were developed many years ago by John Johnson, a scientist at the US Army Night Vision Lab (Night Vision & Electronic Sensors Directorate). Johnson was working to develop methods of predicting target detection, recognition, and identification. He was working with volunteer observers using image intensifier equipment and quantified the volunteer observer's ability to identify scale model targets under various conditions. His experiments produced the first empirical data on perceptual thresholds. The so-called Johnson Criteria have been the basis for many models that predict the performance of sensor systems under different environmental and operational conditions. According to the Johnson Criteria, the minimum resolution (pixels on target) required to achieve a 50% probability that an observer can discriminate an object at a certain range to the specified level are:
 
  • Detection - an object is present: 4 pixels
  • Recognition - the type object can be discerned, a person vs. a car: 16 pixels
  • Identification - a specific object can be discerned, a woman vs. a man, the specific car: 26 pixels
 
 

Disclaimer: We have made every attempt to provide accurate information. However, we cannot accept any responsibility for errors or inaccuracies. Should you require assistance, please contact us directly. Thank you.

Note: modified from electrophysics version by double criteria to be close to real application.

G-Video and  Images Gallary 

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 Video Clip 1         660mm-1680mm  lens

 

 Video Clip 2         660mm-1680mm  lens with Fog filter

Video Clip 3          1000-2000mm lens

 

Video clip 5          300mm, 500mm, 1000mmlens


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