Receive and decode satellite signals using SoapySDR and SGP4 orbital propagation.
npx skills add https://github.com/broomva/skills --skill sdr-satellite
Please help me install this Agent Skill. Skill: sdr-satellite Source: https://github.com/broomva/skills/tree/main/skills/aerospace/sdr-satellite Command: npx skills add https://github.com/broomva/skills --skill sdr-satellite
This skill bridges the gap between raw radio frequency signals and actionable world-state data, allowing you to receive, decode, and visualize satellite transmissions without needing deep expertise in signal processing.
Use the sdr-satellite skill to configure your environment for receiving NOAA-19 weather imagery and predicting its next pass over your location.
High-intent search queries and answers about installing and using this skill.
To decode satellite telemetry, you configure a software-defined radio stack with SoapySDR for hardware abstraction, then process the raw RF signals to extract weather imagery and packet data from satellites like NOAA and Meteor-M.
Yes, you can predict satellite passes and calculate Doppler shifts by integrating SGP4-compliant orbital propagation libraries, which handle the astrodynamics and mechanics needed to track orbits automatically.
The best way to integrate real-time satellite telemetry into an agent-based architecture is to use system integration patterns that wire decoded satellite events directly into frameworks like Opsis or Life Agent OS.
Yes, you need SoapySDR to provide the hardware abstraction layer required to interface with your software-defined radio hardware for receiving NOAA weather imagery and other satellite transmissions.
SGP4 orbital propagation works by using mathematical models of astrodynamics to calculate satellite positions over time, enabling accurate prediction of when a satellite will pass over a specific location and its resulting Doppler shift.
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