Test Results from a Digital P(Y) Code Beamsteering Receiver for Multipath Minimization
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Bibliographic record
Abstract
Scientific Advisory Board for the USAF and serves on the GPS World editorial advisory board. Neil Gerein is a Product Manager for NAVSYS Corporation’s Receivers Group and is responsible for the management and development of NAVSYS ’ next generation of GPS receivers. He is currently completing his M.Sc. in Electrical Engineering and holds a BSEE in Electrical Engineering from the University of Saskatchewan. When using a digital phased array, it is possible to leverage the adaptive spatial signal processing of the array to minimize the effect of multipath signals arriving from near-by reflective surfaces. NAVSYS has developed a digital phased array that can be used for adaptive spatial processing, the High-gain Advanced GPS Receiver (HAGR). Previous testing using the L1 C/A code have demonstrated the performance improvements possible using spatial processing to increase the accuracy of the code and carrier observations and also to minimize the effect of multipath errors. In this paper, we present test results taken from a P(Y) digital beam-steering GPS receiver, the P(Y) HAGR that demonstrates the performance improvements possible for military GPS User Equipment (UE) when using spatial processing to increase accuracy and also to minimize the effect of multipath from near-by reflective surfaces.
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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