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When bad visibility creates strange targets

Fog, rain, dust and haze can change sensor contrast fast enough to create or reshape automated UAP detections.

On this page

  • How visibility changes alter cameras and infrared sensors
  • Near field targets in rain, fog and dust
  • Why event level visibility beats daily forecasts
Preview for When bad visibility creates strange targets

Introduction

A sudden drop in visibility is one of the most important environmental causes of false alarms in automated sky-monitoring systems. Cameras and infrared sensors do not observe the sky directly; they observe light that has travelled through a changing atmosphere. Fog, rain, dust, haze and blowing spray can alter contrast, scatter light, hide parts of an object or create transient bright and dark features within seconds. An automated detector may interpret those changes as the appearance, disappearance or motion of an unusual aerial target when the underlying cause is simply a rapid change in atmospheric transmission. For instrumented UAP detection, this means visibility must be treated as an event-level measurement rather than a background weather note.

Visibility illustration 1

How visibility changes alter cameras and infrared sensors

Visibility affects every stage of automated detection, from image formation to the software that decides whether something deserves an alert.

Visible-light cameras rely heavily on contrast. As fog or haze thickens, distant objects lose edge definition and blend into the background because airborne particles scatter incoming light. Computer vision systems trained to identify moving points or high-contrast edges may therefore see targets fragment, expand or disappear unexpectedly. Studies of camera-based visibility estimation exploit exactly this physical relationship: decreasing visibility is measured through the reduction of contrast between known foreground and background features. [cdn.knmi.nl]cdn.knmi.nlFeasibility study of fog detection and visibility estimationThe dual target approach, which calculates visibility from contrast reduction has proved to…Read more…

Infrared systems are often more resilient than ordinary cameras, but they are not immune. Thermal imagers detect emitted infrared radiation rather than reflected visible light, allowing them to outperform conventional cameras in many low-visibility conditions. However, water droplets, dense fog and heavy precipitation still absorb and scatter infrared energy. Detection range falls, thermal contrast declines and target outlines become less reliable as atmospheric attenuation increases. Laboratory and field studies have demonstrated clear operational limits beyond which even thermal cameras become unreliable. [PMC+2MDPI]pmc.ncbi.nlm.nih.govAnalysis of Thermal Imaging Performance under Extreme…by JMR Velázquez · 2022 · Cited by 44 — In this paper, an analysis of the res…

For automated UAP detectors this creates two related risks:

  • A genuine aircraft or astronomical object may fade until only fragments remain, causing unstable tracking.
  • Random fluctuations in brightness or thermal contrast may briefly exceed the detector’s alert threshold, creating a false target.

Neither outcome necessarily indicates an unusual object. Both can result from changing atmospheric transmission.

Infrared Camera

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Near-field targets become convincing when rain, fog or dust reduce context

Poor visibility changes more than the appearance of distant objects. It also removes the visual cues that normally help software estimate distance and scale.

In clear air, background stars, cloud texture or horizon features help distinguish a nearby insect from a distant aircraft. When fog or heavy rain removes those references, a nearby object crossing close to the camera may appear isolated against a featureless background. Motion that is actually only a few centimetres from the lens can then be interpreted as movement across a much larger volume of sky.

Several mechanisms become more common during deteriorating visibility:

  • Rain droplets near the optics can briefly brighten from external lighting or moonlight and trigger motion algorithms.
  • Fog droplets scatter point sources, producing expanding halos whose apparent size changes as visibility changes.
  • Dust or airborne debris passing close to the camera can appear unusually bright or sharply defined while distant scenery fades.
  • Wind-driven precipitation creates rapidly evolving streaks that automated trackers may temporarily classify as coherent moving objects.

The common feature is that atmospheric degradation suppresses reliable background information while increasing local optical artefacts. Detection software may therefore become more confident about the wrong object.

Infrared imagery experiences related but different effects. Rain, fog and high humidity reduce thermal contrast between targets and their surroundings. When environmental temperatures approach target temperatures, the distinction between object and background becomes increasingly ambiguous, making automatic segmentation less reliable. [PMC]pmc.ncbi.nlm.nih.govTherefore, Infrared radiation is less affected in…Read more…

Visibility illustration 2

Why event-level visibility beats daily forecasts

One of the easiest mistakes in UAP analysis is assuming that a daily weather summary adequately describes observing conditions.

Visibility can change dramatically over only a few minutes as fog banks form, showers pass or blowing dust crosses the field of view. Aviation meteorology treats these changes as operationally significant. METAR observations describe routine conditions, while SPECI reports are issued when important weather elements such as visibility, cloud base, precipitation or wind change beyond specified thresholds because those changes directly affect safe observation and navigation. [Bureau of Meteorology+2Federal Aviation Administration]bom.gov.aumetar speciBureau of MeteorologyMETAR/SPECIJune 18, 2024 — SPECI is used to identify reports of observations when: • conditions are below specified…Published: June 18, 2024

The same principle applies to automated sky-monitoring stations.

An alert generated at 21:17 may have little relationship to a weather observation issued at 21:00 if visibility collapsed during the intervening minutes. Event-level analysis should therefore combine the detection timestamp with:

  • local visibility measurements,
  • precipitation intensity,
  • humidity, * cloud-base observations, [bom.gov.au]bom.gov.aumetar speciBureau of MeteorologyMETAR/SPECIJune 18, 2024 — SPECI is used to identify reports of observations when: • conditions are below specified…Published: June 18, 2024 * present-weather sensors, [canada.ca]canada.caManual of Surface Weather Observation Standards…METAR contains a report of wind, visibility, runway visual range, present weather, sky…
  • and, where available, camera-derived visibility estimates.

Camera-based visibility estimation has become an active research area precisely because local atmospheric transmission can vary significantly across short distances and short time periods. Systems that estimate visibility directly from the recorded imagery can provide information unavailable from regional forecasts alone. [MDPI]mdpi.comThe best performing model reached a score level of 0.89…Read more…

Helping Cameras See Clearly With AI - NVIDIA DRIVE Labs Ep. 3

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Why sudden visibility loss produces misleading motion

Visibility changes rarely affect an entire image uniformly.

A fog bank moving across the field of view may obscure only one side of a target. Rain shafts can selectively attenuate one portion of an image while leaving another nearly unchanged. Haze frequently develops in uneven layers.

This non-uniform attenuation creates several misleading signatures:

  • targets appear to accelerate as their brightest portion shifts;
  • tracks become discontinuous because detection confidence fluctuates;
  • apparent shape changes occur as only part of an object remains visible;
  • automated trackers may abandon one target and initialise another nearby, creating an illusion of abrupt manoeuvres.

These behaviours are familiar challenges in machine vision research for autonomous vehicles and long-range surveillance, where adverse weather substantially increases false detections unless environmental conditions are explicitly incorporated into the perception pipeline. [PMC+2arXiv]pmc.ncbi.nlm.nih.govPMCVisibility Enhancement and Fog DetectionIn mobile systems, fog, rain, snow, haze, and sun glare are natural phenomena that can be very dangerous for drivers.Read more…

For UAP detection systems, the lesson is similar: unexplained motion should not be evaluated independently of simultaneous changes in atmospheric visibility.

Visibility illustration 3

A detector cannot eliminate poor weather, but it can recognise when atmospheric conditions reduce confidence in its own observations.

Useful design practices include:

  • recording local visibility continuously rather than relying on regional forecasts;
  • logging humidity, precipitation and present-weather measurements alongside every alert;
  • lowering confidence in detections when image-wide contrast drops rapidly;
  • comparing visible and thermal imagery rather than trusting either independently;
  • checking whether background landmarks lose contrast at the same time the target appears;
  • retaining the full environmental record so analysts can distinguish sensor artefacts from genuinely unexplained events.

Rather than treating visibility as a secondary weather variable, robust automated UAP systems benefit from treating it as part of the sensor itself. Every camera observes through the atmosphere, and rapid changes in that atmosphere can reshape what the detector believes it has seen long before any unusual aerial object needs to be considered.

Estimating Fog Parameters From an Image Sequence Using Non-Linear Optimisation

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Endnotes

  1. Source: cdn.knmi.nl
    Title: Feasibility study of fog detection and visibility estimation
    Link: https://cdn.knmi.nl/knmi/pdf/bibliotheek/knmipubIR/IR2015-05.pdf
    Source snippet

    The dual target approach, which calculates visibility from contrast reduction has proved to...Read more...

  2. Source: pmc.ncbi.nlm.nih.gov
    Link: https://pmc.ncbi.nlm.nih.gov/articles/PMC9699133/
    Source snippet

    Analysis of Thermal Imaging Performance under Extreme...by JMR Velázquez · 2022 · Cited by 44 — In this paper, an analysis of the res...

  3. Source: mdpi.com
    Link: https://www.mdpi.com/1424-8220/19/15/3313
    Source snippet

    Thermal Imager Range: Predictions, Expectations, and...by D Perić · 2019 · Cited by 97 — Imaging system range defines the maximal distan...

  4. Source: pmc.ncbi.nlm.nih.gov
    Link: https://pmc.ncbi.nlm.nih.gov/articles/PMC11193785/
    Source snippet

    Therefore, Infrared radiation is less affected in...Read more...

  5. Source: mdpi.com
    Link: https://www.mdpi.com/2073-4433/13/10/1684
    Source snippet

    The best performing model reached a score level of 0.89...Read more...

  6. Source: pmc.ncbi.nlm.nih.gov
    Title: PMCVisibility Enhancement and Fog Detection
    Link: https://pmc.ncbi.nlm.nih.gov/articles/PMC8150865/
    Source snippet

    In mobile systems, fog, rain, snow, haze, and sun glare are natural phenomena that can be very dangerous for drivers.Read more...

  7. Source: arxiv.org
    Title: arXiv Towards Robust 3D Object Detection In Rainy Conditions
    Link: https://arxiv.org/abs/2310.00944

  8. Source: weather.gov
    Title: metar decode key
    Link: https://www.weather.gov/media/wrh/mesowest/metar_decode_key.pdf
    Source snippet

    METAR ABBREVIATIONS24 Dec 2008 — TORNADIC ACTIVITY: Augmented; report should include TORNADO, FUNNEL CLOUD, or WATERSPOUT, time begin/end...

  9. Source: bom.gov.au
    Title: metar speci
    Link: https://www.bom.gov.au/aviation/data/education/metar-speci.pdf
    Source snippet

    Bureau of MeteorologyMETAR/SPECIJune 18, 2024 — SPECI is used to identify reports of observations when: • conditions are below specified...

    Published: June 18, 2024

  10. Source: faa.gov
    Title: Federal Aviation Administration Chapter 7
    Link: https://www.faa.gov/air_traffic/publications/atpubs/aim_html/chap7_section_1.html
    Source snippet

    Chapter 7. Safety of FlightThe FAA maintains an extensive surface weather observing program. Airport observations (METAR and SPECI) in th...

  11. Source: whitepapers.axis.com
    Title: thermal cameras
    Link: https://whitepapers.axis.com/en-us/thermal-cameras
    Source snippet

    cameras - White papers - Axis CommunicationsRain, fog, and smog reduce the detection range. The rate of thermal radiation attenuation dep...

Additional References

  1. Source: researchgate.net
    Link: https://www.researchgate.net/publication/365282047_Analysis_of_Thermal_Imaging_Performance_under_Extreme_Foggy_Conditions_Applications_to_Autonomous_Driving
    Source snippet

    Analysis of Thermal Imaging Performance under Extreme...Nov 2, 2022 — In this paper, an analysis of the resilience of thermal sensors in...

  2. Source: icao.int
    Link: https://www.icao.int/sites/default/files/APAC/Meetings/2024/2024%20METR%20WG-13%20%26%20MET-ATM%20Seminar/MET-R%20WG-13/4-Information%20Papers/IP08_AI3_HKG_REPRESENTATIVENESS-OF-WEATHER-OBSERVATIONS-AT-HKG-INTL-APT-UNDER-THREE-RUNWAY-SYS.pdf
    Source snippet

    MET R WG/13 – IP/08This paper discusses the factors that have been considered when selecting weather elements, specifically winds and RVR...

  3. Source: canada.ca
    Link: https://www.canada.ca/en/environment-climate-change/services/weather-manuals-documentation/manobs-surface-observations.html
    Source snippet

    Manual of Surface Weather Observation Standards...METAR contains a report of wind, visibility, runway visual range, present weather, sky...

  4. Source: wiki.ivao.aero
    Link: https://wiki.ivao.aero/en/home/training/documentation/metar_explanation
    Source snippet

    explanation | IVAO Documentation LibraryMETAR is local routine and special reports in abbreviated plain language intended for disseminati...

  5. Source: aphys.kth.se
    Link: https://www.aphys.kth.se/polopoly_fs/1.934189.1600690015%21/Thesis_Josefine_Ulrika.pdf
    Source snippet

    of IR transmittance in different weather...by J CORNÉ · Cited by 5 — The infrared imaging system was shown to perform well during approa...

  6. Source: researchgate.net
    Link: https://www.researchgate.net/publication/381639350_The_research_on_infrared_radiation_affected_by_smoke_or_fog_in_different_environmental_temperatures
    Source snippet

    The research on infrared radiation affected by smoke or fog...20 Jun 2024 — Infrared thermal imaging camera as a non-contact monitoring...

  7. Source: skybrary.aero
    Link: https://skybrary.aero/articles/weather-observations-aerodromes

  8. Source: news.ncac.mn
    Link: https://news.ncac.mn/uploads/bookSubject/2022-11/63772f4497d98.pdf
    Source snippet

    on Automatic Meteorological Observing Systems at...Visibility in a METAR/SPECI must be representative of the aerodrome, which is a wide...

  9. Source: swi-wiskunde.nl
    Link: https://www.swi-wiskunde.nl/swi2016/wp-content/uploads/sites/3/2017/07/knmi.pdf
    Source snippet

    Multiple methods are possible for determining an effective value for the contrast. We were not...Read more...

  10. Source: anvil.so
    Link: https://anvil.so/post/ultimate-guide-to-environmental-factors-in-thermal-imaging
    Source snippet

    Ultimate Guide to Environmental Factors in Thermal ImagingJan 19, 2025 — Weather: Rain, fog, and high humidity can reduce image clarity...

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