Super-Resolution GPS Receiver: User's Acceleration Computation
Bibliographic record
Abstract
Current commercial global navigation satellite system (GNSS) receivers cannot measure the change of Doppler shift via baseband processing. However, positioning in challenging environments demands accurate Doppler estimates to replicate the actual intermediate-frequency (IF) line-of-sight (LOS) GNSS signals. Otherwise, the instantaneous GNSS measurements, like pseudoranges and carrier phases, will be seriously distorted, restricting the upper bound of GNSS positioning. This paper proposes a brand-new super-resolution (SR) GNSS receiver that computes the user's absolute acceleration based on super-long coherent integration (S-LCI), fractional Fourier transform (FRFT), and a baseband maximum likelihood estimator (MLE). A basic nonlinear least square (NLS) navigator taken as an intuitive example shows how the proposed receiver models and generates averaging Doppler rates via the baseband-dependent gradient descent (GD) algorithm. A global positioning system (GPS) software-defined radio (SDR) processing the L5 IF data collected via a mobile cart in the real world validates the proposed technique with the Doppler rate measurement, the user's acceleration navigation solution, and the clock drift rate.
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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 | 0.001 |
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".