🚀 interplanetary-mission-sim: JPL Horizons N-Body Suite

A high-fidelity orbital mechanics environment that bridges real-world NASA ephemeris data with a 3D N-body gravitational engine. This suite allows for the planning and execution of interplanetary transfers, featuring a functional "Flight Computer" for trajectory correction and orbital insertion.

🛠 Project Architecture

The project is split into two specialized modules to maintain professional data separation:

1. fetch_horizons_data.py (The Data Fetcher): Uses the astroquery.jplhorizons library to pull precise position and velocity vectors directly from NASA's JPL Horizons system. It exports this state to objects.json.

2. main.py (The Simulation Engine): A 3D Matplotlib-based engine that simulates gravitational interactions using Newton's Law of Universal Gravitation and provides a real-time HUD for mission control.

🔬 Physics & Engineering Features

• N-Body Gravity: Unlike simple 2-body models, this sim calculates the gravitational pull from the Sun and all active planets on the spacecraft simultaneously.

• Flight Computer: * Shooting Method: The "FIX PATH" feature uses iterative simulation to calculate the necessary $\Delta V$ (velocity change) to intercept Mars.

  • B-Plane Targeting: Calculates a safety offset (6,000 km radius) to ensure the spacecraft achieves a safe flyby altitude rather than a direct impact.

• Variable Precision Integrator: Uses a dynamic time-stepping logic that increases calculation frequency (precision) when a spacecraft is in close proximity to a planetary body.

🎮 Mission Control UI

• Navigation: Focused view modes for all major planets and "Top-Down" ecliptic perspectives.

• Propulsion: Manual Prograde/Retrograde burn controls and a custom $\Delta V$ vector launch panel.

• Telemetry HUD: Real-time display of altitude, relative velocity, and estimated periapsis during planetary approach.

🚀 Getting Started

1. Requirements

Bash

pip install numpy matplotlib astroquery

2. Update Data (Optional)

Run the fetcher to get the latest planetary positions from NASA:

Bash

python fetch_horizons_data.py

3. Run Simulation

Bash

python main.py

📈 Roadmap for Professional Alignment

• Integrator Upgrade: Move from Euler-based stepping to a Runge-Kutta (RK4) integrator for long-term orbital stability.

• Non-Spherical Gravity: Implement J2 Perturbations for high-accuracy Low Earth Orbit (LEO) modeling.

• Relativistic Effects: Add Schwarzschild metric corrections for high-precision Mercury orbits.