Model
EV3000-D-IR250 EV3000-D-IR500 EV3000-D-IR750 EV3000-D-IR1100
Pixel
pitch (µm)
H
(µm)
V
(µm)
Number
of Pixels
H-pixels
V-pixels
Detector
Size (mm)
H-size
V-size
9.60
7.68
Field of
View
Lens focal
length
mm
Enter
250 for EV3000-D-IR250
Enter
500 for EV3000-D-IR500 default
Enter
750 for EV3000-D-IR750
Enter
1100 for EV3000-D-IR1100
Field
of View (FOV) (degrees) °
H-FOV
V-FOV
D-FOV
0.73
0.58
0.93
Pixel
Field of View (IFOV) (mrad)
H-FOV
V-FOV
0.03
0.03
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
13.00
11.00
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
4.06
4.29
Range
H-Size of
object
meters
Enter
target size and click here
Max
Detection Range (4 pixels)
% of display
Range (meters)
% of H display
5000.00
0.62%
Max
Recognition Range (16 pixels)
% of display
Range (meters)
% of H display
1250.00
2.50%
Max
Identification Range(26 pixels)% of display
Range (meters)
% of H display
769.23
4.06%
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.