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Loading...Introduction to Orbital Debris Tracking
Last quarter, our team discovered that tracking orbital debris was crucial for satellite safety. We tried using Python 3.12, Pandas 2.0, and Scipy 1.10 to implement both Kalman Filter and UKF algorithms. Here's what we learned.
The Problem of Orbital Debris
Orbital debris poses a significant threat to operational spacecraft. With thousands of pieces of debris in Earth's orbit, the risk of collision is high. To mitigate this risk, accurate tracking of debris is essential.
Kalman Filter Implementation
We first implemented a Kalman Filter using Scipy 1.10. The Kalman Filter is a mathematical method for estimating the state of a system from noisy measurements. It's widely used in navigation and control systems.
import numpy as np
from scipy.linalg import inv
# Define the state transition matrix
A = np.array([[1, 1], [0, 1]])
# Define the measurement matrix
H = np.
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- Complete step-by-step implementation guide
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- Real-world examples and metrics
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