Kalman filter based ranging and clock synchronization for ultra wide band sensor networks
Why this work is in the frame
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Bibliographic record
Abstract
This Thesis presents the design, implementation, and validation of a Kalman filterbased range estimation technique to precisely calculate the inter-node ranges of Ultra Wide Band (UWB) modules. In addition to that the development and validation of an improved global clock synchronization framework is presented. Noise characteristics of relative time measurements of a stationary UWB anchor pair are first analyzed using an Allan deviation plot. To track the propagation of the imprecise clocks on low cost UWB transceiver platforms, Kalman filters are used in between every anchor pair. These filters track the variation of a remote anchor’s hardware clock relative to it’s own hardware clock, while estimating the time of flight between the anchor pair as a filter state. While adhering to a simple round robin transmission schedule, both inbound and outbound message timestamp data are used to update the filter. These measurements have made the time of flight observable in the chosen state space. A faster relative clock filter convergence has been achieved with the inclusion of the clock offset ratio as a measurement additional to the timestamps. Furthermore, a modified gradient clock synchronization algorithm is used to achieve global clock synchronization throughout the network. A correction term is used in the gradient clock synchronization algorithm to enforce the global clock rate to converge at the average of individual clock rates while achieving asymptotic stability in clock rate error state. Stability of the original and modified methods for time invariant hardware clocks are compared using eigenvalue tests. Experiments are conducted to evaluate synchronization and ranging accuracy of the proposed range estimation approach.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it