THE UNIVERSITY OF CALGARY Mitigation of Narrow Band Interference on Software Receivers based on Spectrum Analysis
Bibliographic record
Abstract
This thesis describes an extensive investigation into the development of a narrow-band radio frequency interference (RFI) mitigation algorithm and performance testing using a software Global Positioning System (GPS) receiver. Traditionally, most RFI mitigation methods have been implemented and tested using conventional hardware receivers. With the rapid development of computer technologies, the signal processing computational load is becoming less of a concern, and thus it becomes feasible to develop and test new interference mitigation methods based on software receivers together with modern digital signal processing techniques. In this research, a narrow-band RFI mitigation algorithm based on spectrum analysis is discussed in the acquisition, tracking and position domains. A series of hardware simulation tests is conducted to assess the performance of this algorithm. For high level interference, a fixed detection threshold as previously suggested in the literature is not sufficient. An adaptive detection threshold that is
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".