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Learning Antenna Pointing Correction in Operations: Efficient Calibration of a Black Box

Leif Bergerhoff

TL;DR

This work uses a standard antenna interface and data from an operational satellite contact to come up with a robust strategy for training data set generation and learns the parameters of a suitable coordinate transform by means of linear regression.

Abstract

We propose an efficient offline pointing calibration method for operational antenna systems which does not require any downtime. Our approach minimizes the calibration effort and exploits technical signal information which is typically used for monitoring and control purposes in ground station operations. Using a standard antenna interface and data from an operational satellite contact, we come up with a robust strategy for training data set generation. On top of this, we learn the parameters of a suitable coordinate transform by means of linear regression. In our experiments, we show the usefulness of the method in a real-world setup.

Learning Antenna Pointing Correction in Operations: Efficient Calibration of a Black Box

TL;DR

This work uses a standard antenna interface and data from an operational satellite contact to come up with a robust strategy for training data set generation and learns the parameters of a suitable coordinate transform by means of linear regression.

Abstract

We propose an efficient offline pointing calibration method for operational antenna systems which does not require any downtime. Our approach minimizes the calibration effort and exploits technical signal information which is typically used for monitoring and control purposes in ground station operations. Using a standard antenna interface and data from an operational satellite contact, we come up with a robust strategy for training data set generation. On top of this, we learn the parameters of a suitable coordinate transform by means of linear regression. In our experiments, we show the usefulness of the method in a real-world setup.
Paper Structure (14 sections, 9 equations, 7 figures, 2 tables)

This paper contains 14 sections, 9 equations, 7 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Our Contributions
  3. Structure of the Paper
  4. Technical Background
  5. Theory and Modeling
  6. Experiments and Calibration Strategy
  7. Step Track
  8. Training
  9. Testing
  10. Improved Calibration Strategy
  11. Improved Calibration
  12. Training
  13. Testing
  14. Summary and Outlook

Figures (7)

  • Figure 1: Exemplary antenna pointing towards the DSCOVR satellite.
  • Figure 2: The basic evaluation process for antenna pointing quality.
  • Figure 3: Pointing direction type and measured signal level. Top: Used angle type over time for step track testing. Middle: Step track test setup. Bottom: Reevaluation of the learned matrix $\mathbf{T}$ and detection of maxima positions.
  • Figure 4: Process of using our software-based antenna pointing correction.
  • Figure 5: Estimated and learned offsets using the improved calibration strategy. Top: Azimuth angle offsets. Bottom: Elevation angle offsets.
  • ...and 2 more figures