Experimental carrier detection of BPSK and QPSK direct sequence spread spectrum signals
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Bibliographic record
Abstract
This paper reports on an experimental investigation of the detection of BPSK and QPSK direct sequence (DS) spread spectrum signals above and below the noise floor using nonlinear carrier detection methods. These processes produce carrier harmonics 2f/sub 0/ and 4f/sub 0/ for BPSK and QPSK signals respectively. The signal-to-noise ratio of these harmonics depends on the input signal signal-to-noise ratio, SNR (chip symbol energy/noise power density), normalized input bandwidth, /spl eta/(input filter bandwidth/chip rate) and interceptor's process gain, R/B (chip rate/detection bandwidth). Measurements agree well with analytic expressions. At low input SNR, the signal-to-noise ratio of the carrier harmonics is maximized for /spl eta/=1.0 and varies as SNR/sup 2/ for BPSK signals and in the range of SNR/sup 3/ to SNR/sup 4/ for QPSK signals (the theoretical limit /spl prop/SNR/sup 4/ is only sometimes reached in practice.) QPSK signals generated from typical commercial quadrature modulators may also be detected at If/sub 0/ from mixer LO leak-through and at 2f/sub 0/ from I/Q channel imbalance. For LPI use of QPSK DS signals, the LO leak-through must be carefully suppressed to <-55 dB and the two channels balanced within 0.2 dB. For a typical R/B=60 dB (10 MHz chip rate detected in a 10 Hz detection bandwidth), the threshold of detection is an SNR of -23 dB for BPSK signals and -8 dB for QPSK signals.
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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 | 0.001 | 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