High-Accuracy Localization Platform Using Asynchronous Time Difference of Arrival Technology
Why this work is in the frame
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Bibliographic record
Abstract
Despite extensive research efforts on ranging and localization modeling and simulation, research on practical implementations is limited. For the first time, a complete prototype based on asynchronous time difference of arrival (A-TDOA) technique is implemented in hardware. The A-TDOA technique requires neither clock synchronization between a target and anchor nodes nor wired infrastructure among anchor nodes, both of which are necessary for time of arrival and TDOA systems, respectively. All subsystems, including transmitter, receiver, antenna, and baseband processing unit, are developed from scratch and undergone significant updates for improved reliability. The implemented system has been extensively tested in an outdoor and indoor line of sight radio environments, and the accuracies obtained are 20.7 and 15.2 cm in 8 m × 8 m and 6 m × 6 m areas, respectively. In nonline of sight indoor environment, the achieved accuracy is 21.3 cm in 5 m × 5 m area. The comparison with the literature published to date proves the excellent quality of these results. To better understand the localization accuracy, the error sources due to thermal noise, hardware limitation, and radio propagation channel are identified and investigated. Mitigation methods are proposed to reduce errors. The implemented prototype supports many unique applications including cargo tracking, tourist guiding, emergency evacuation, and so on.
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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 | 0.000 | 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 it