Detection Performance of Polarization and Spatial Diversities for Indoor GNSS Applications
Bibliographic record
Abstract
Multipath fading in the form of signal power fluctuation poses a formidable challenge to GNSS signal detection in harsh multipath environments such as indoors. Antenna diversity techniques such as polarization and spatial diversities can be used to combat multipath fading in wireless propagation channels. This paper studies and compares GPS signal detection performance enhancements arising from the spatial and polarization diversity techniques. Performance enhancements are quantified from a theoretical perspective and later verified based on several test measurements in various indoor environments. Enhancement is quantified based on measuring the correlation coefficient values between diversity branches, SNR levels, and computing the level crossing rate and average fade duration. In addition, the processing gain is quantified and the performance of each individual diversity system is evaluated. Experimental results show that, for a given target detection performance in terms of the probability of false alarm and the probability of detection, the required input SNR level to meet the target detection performance can be significantly reduced utilizing the diversity system.
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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".