Real data from the public satellite catalog

Know which conjunctions actually matter.

OrbitalGuard ingests public satellite catalog data, propagates trajectories, and screens for close approaches, giving CubeSat teams, researchers, and small operators clear, sourced risk assessments without a flight-dynamics department.

No signup needed. One click into a shared demo account with real, live catalog data. Or create your own free account.

OrbitalGuard's 3D orbital map showing tracked satellites around a live Earth globe
Real-time 3D orbital map Live
…
Tracked objects
…
Screened encounters (7d)
…
Data source

Data sourced from publicly available catalogs, starting with CelesTrak

Who it's for

Built for teams without a flight-dynamics department

CubeSat teams

Get conjunction screening and watchlist alerts on your own spacecraft without standing up a flight-dynamics team.

Researchers

Explore public-catalog orbital data with transparent methodology: every number shows its data source, epoch, and age.

Satellite operators

Monitor specific objects, track how conjunction risk evolves over time, and get explainable, sourced risk classifications.

Core capabilities

Everything you need to monitor collision risk

01

Track

See tracked objects around a real-time 3D Earth globe with orbit paths, filtering, and search, powered by CesiumJS.

02

Analyze

Broad-phase candidate filtering followed by numerical TCA refinement produces explainable LOW/WATCH/ELEVATED/HIGH risk labels, never a bare score.

03

Monitor

Add objects to a watchlist and track how their conjunction risk evolves over time, with a full history of past encounters.

04

Alert

Get notified in-app when a monitored object's risk crosses a threshold you set, with spam-safe deduplication.

See the product

Real screens, real catalog data

Every screenshot below is the live product against real, ingested CelesTrak data. Nothing is staged.

OrbitalGuard 3D orbital map with a tracked object selected, showing its catalog source and data age

3D orbital map

Track real objects around a live Earth globe, powered by CesiumJS and public catalog data.

OrbitalGuard dashboard showing tracked objects, encounters, risk overview, and data sources

Dashboard

A live overview of tracked objects, screened encounters, and data freshness at a glance.

OrbitalGuard conjunctions table showing predicted close approaches with risk, miss distance, and TCA

Conjunctions

Every predicted close approach, with miss distance, relative velocity, and time to closest approach.

OrbitalGuard watchlist detail showing monitored objects, an active alert rule, and risk history

Watchlist

Monitor specific objects, set alert thresholds, and see how their risk has changed over time.

Try it yourself

The ISS conjunction workflow, end to end

Every step below uses the same catalog data shown in the demo. Nothing is staged.

01

Search a satellite

Find any publicly catalogued object, try "ISS", and see its current position, altitude, speed, and data freshness.

02

See predicted close approaches

OrbitalGuard screens the catalog and shows encounters with TCA, miss distance, relative velocity, and why each was classified the way it was.

03

Watch it and get alerted

Add objects to a watchlist, set a risk threshold, and get an in-app alert when something changes, with risk history to see the trend.

Methodology

How the numbers are actually calculated

OrbitalGuard performs public-data screening. It supports decision-making; it is not a replacement for operational conjunction assessment or a qualified flight-dynamics process.

Propagation uses SGP4 against mean orbital elements from public GP/OMM data. Accuracy degrades as the element set ages, every object shows its source epoch and data age.

Time of Closest Approach is found by numerically minimizing SGP4-propagated relative distance. Broad-phase orbital-shell and coarse-sampling filters narrow candidates first, then a golden-section search converges on the precise minimum.

Risk levels (LOW / WATCH / ELEVATED / HIGH) are OrbitalGuard-defined thresholds from miss distance and relative velocity, not an international standard, and every classification lists its specific reasons.

Collision probability is never fabricated. Pc requires covariance/uncertainty data not present in public TLE/OMM data, so it is not computed. The product says so explicitly rather than guessing.

Today: CelesTrak

Scheduled ingestion of CelesTrak's GP/OMM and SATCAT data. Object elements, classification, launch/decay status, and operator info, refreshed on a per-source-group basis.

Designed to extend

The ingestion architecture is provider-agnostic by design, built to add Space-Track, CCSDS CDM feeds, operator ephemerides, or commercial SSA data without re-architecting the core.

Limitations

What this product is not

Stated plainly, because collision risk software that oversells itself is dangerous.

  • Only sees objects present in its configured data sources, not “all space debris.”
  • Public GP/TLE/OMM screening is not operational-grade conjunction assessment.
  • No collision probability is fabricated. Pc requires covariance data this product doesn't have yet.
  • Decision-support only. Real spacecraft safety decisions require authoritative conjunction data and a qualified flight-dynamics process.

See it running on real data

One click, no signup. This demo runs on the same catalog data as the full product.