Summary：A common question customers ask when purchasing infrared thermal imagers is: How far can an infrared thermal imager see? This is a crucial question, yet difficult to answer definitively. For example, a thermal imager might be able to see the sun at a distance of 146 x 10⁶ kilometers, but that doesn't mean its detection range is 146 x 10⁶ kilometers. However, this detection range is a crucial point that must be clarified, as customers buying infrared thermal imagers.
When purchasing an infrared thermal imager, users often ask: "How far can it see?" This is a crucial question, yet one that is difficult to answer precisely. For instance, while a thermal imager can "see" the sun—located 146 million kilometers away—one cannot claim the device has a detection range of 146 million kilometers. Nevertheless, defining detection range is essential, as customers purchase these devices to detect and monitor specific targets. Let us examine the Johnson Criteria to understand how target detection range is determined.
The Johnson Criteria: Detection range is the result of an interplay between subjective and objective factors. Subjective factors relate to the observer's visual psychology and experience. To answer "how far a thermal imager can see," one must first define what it means to "see clearly." Since one person might consider a target "clearly seen" while another does not, an objective, standardized evaluation criterion is required. Extensive research has been conducted in this field; based on experimental data, Johnson linked the issue of target detection to the concept of equivalent bar patterns. Many studies have demonstrated that—without considering the specific nature of the target or image artifacts—the resolution of equivalent bar patterns can be used to determine an infrared imaging system's ability to identify targets. This concept forms the basis of the Johnson Criteria.
Target detection is categorized into three levels: detection (discovery), recognition, and identification.
A. Detection: Defined as spotting a target within the field of view. At this stage, the target's image must occupy at least 1.5 pixels along its critical dimension.
B. Recognition: Defined as classifying the target—for example, distinguishing whether it is a tank, a truck, or a person. At this stage, the target's image must occupy at least 6 pixels along its critical dimension.
C. Identification: Defined as distinguishing the target's specific model and other characteristics—such as differentiating between friend and foe. At this stage, the target's image must occupy at least 12 pixels along its critical dimension. The data above is based on a 50% probability—meaning the target is just barely detectable—and a target-to-background contrast ratio of 1. As the Johnson Criteria indicate, the detection range of an infrared thermal imager is determined by factors such as target size, lens focal length, and detector performance.
Factors determining detection range:
1. Lens Focal Length: Lens focal length is the most critical factor determining a thermal imager's detection range. It directly dictates the size of the target image—specifically, how many pixels the image occupies on the focal plane. This is typically expressed via Instantaneous Field of View (IFOV), which represents the angular span of each pixel in object space (i.e., the minimum angle the system can resolve). IFOV is generally calculated as the ratio of pixel size (d) to focal length (f): IFOV = d/f. The number of pixels occupied by the target image on the focal plane can be calculated using the target size, the distance between the target and the imager, and the IFOV. Dividing the target's angular span (the ratio of target size D to distance L) by the IFOV yields the number of pixels occupied (n): n = (D/L) / IFOV = (Df) / (Ld). This shows that a longer focal length results in the target image occupying more pixels, which—according to the Johnson Criteria—allows for a greater detection range. However, a longer focal length also results in a narrower field of view and higher costs. Consider this example: a thermal imager with a focal plane pixel size of 38 μm and a 100 mm lens has an IFOV of 0.38 mrad. When observing a 2.3 m target at a distance of 1 km, the target's angular span is 2.3 mrad, and the resulting image occupies 2.3 / 0.38 = 6 pixels. According to the Johnson Criteria, this meets the threshold for target identification.
2. Detector Performance: While lens focal length theoretically determines the detection range, detector performance is another crucial factor in practical application. Lens focal length merely determines the image size and pixel count; detector performance determines image quality, such as the level of blurriness and the signal-to-noise ratio. Detector performance can be analyzed in terms of pixel size, thermal sensitivity, and signal processing. A smaller pixel size results in finer spatial resolution (IFOV); as previously discussed, this translates to a greater detection range. A classic example is found in FLIR’s uncooled thermal cameras: the Photon 320 has a pixel size of 38 μm, while the Photon 640 has a pixel size of 25 μm. When both are equipped with a 100mm lens and used to observe a 2.3-meter target, the Johnson criteria indicate identification ranges of 1 km and 1.5 km, respectively. Image clarity is determined by the detector's thermal sensitivity and signal processing capabilities; if these are inadequate, the resulting image will be a blurry thermal representation, making identification impossible. Consequently, when a detector lacks sufficient thermal sensitivity, increasing the lens aperture is one method used to improve image quality—though this approach raises costs and reduces operational convenience. In contrast, the F-number of lenses used with FLIR’s Photon series can typically be reduced to the 1.4–1.7 range, allowing for exceptionally small apertures.
3. Atmospheric Environment: Although thermal radiation penetrates the atmosphere more effectively than visible light, atmospheric absorption and scattering still impact thermal imaging—particularly during heavy fog or rain—thereby affecting the camera's detection range. In summary, determining exactly "how far" a thermal camera can see is complex, as the result is shaped by a combination of objective factors—such as the detector, lens, target, and atmospheric conditions—and subjective human factors.
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