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Real-Time Satellite Tracking and Intelligence Dashboard

Hacker News

Real-Time Satellite Tracking and Intelligence Dashboard

Hey HN, We built Heimdall (heimdallspace.com) because the existing tools for space situational awareness are genuinely painful to use: clunky interfaces, fragmented data sources, slow rendering. The ones that aren't are locked behind enterprise solutions. We thought the foundation of this should be open and accessible. The goal is a satellite observability platform: one place that gives operators complete, real-time insight into their assets and the orbital environment around them. Today's release is the foundation—aggregating and rendering the full public space catalog (30,000+ objects) in real time. How it works technically: - SGP4 propagation running across web workers, computing positions every few frames - Go backend ingesting TLEs hourly from Space-Track.org with daily metadata enrichment from GCAT - React + Three.js frontend rendering 30,000+ objects as GPU point sprites with custom GLSL shaders - 8K Earth textures with accurate solar-positioned day/night cycle - Self-hosted on a VPS Any feedback is appreciated. We'd also love technical feedback on the propagation approach, data pipeline, or anything that looks wrong or could be done better. We're looking for professionals in the space industry who might be able to provide real-world insight into what they want from the platform. We're early and building in the open, so this is a real ask.

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
86%86% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: open · Missing: mac, agents, macos
75%75% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: exist, existing, ide · Missing: https docs, excited, just released
55%55% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, host, interface · Missing: plus, intuitive, reviews
49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: real time · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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