Bibliographic record
Abstract
The next generation of guided radar (GUIDAR) is based on ultra wide band (UWB) radar signal processing. Just as spread spectrum technology has revolutionized the communications industry UWB is dramatically changing radar signal processing. These advanced signal processing techniques are adapted to leaky coaxial cable technology in the next generation GUIDAR to provide new features and enhanced performance. At the core of the new technology is an ultra high-speed digital correlator implemented in a field programmable gate array (FPGA). Complementary orthogonal codes based on Golay codes are used to produce thumbtack correlation functions simultaneously in multiple range bins. The net result is "near continuous wave (CW)" performance (97% duty cycle) in forty to eighty 11.6-meter long-range bins with targets located within one meter along the length of cable. This is a dramatic improvement over the 3% duty cycle of the original GUIDAR and the typical 100 to 200 meter long zones of current CW leaky cable sensors. Orthogonal complementary codes are transmitted on each of two leaky coaxial cables. The responses from the parallel receive cables are fed to a direct digital receiver. The orthogonal nature of the code allows the composite coded pulse response to be de-multiplexed into the independent response for each of the two cables. This ultra-high speed correlation process involves the addition and subtraction of the sampled in-phase and quadrature-phase responses to the multiple range bin accumulators at 10 million samples per second. Synchronous sampling at twice the chip rate ensures that each target is observed in three adjacent sample bins. The phase and amplitude response in the three adjacent samples are combined to precisely pinpoint (within 1 meter) the locations of targets along the length of each of the two cables. The ability to precisely locate and track multiple simultaneous targets on each of two cables leads to numerous new features and performance benefits relative to existing leaky cable sensors. With a separate calibrated threshold for every meter of cable the sensor sensitivity is much more uniform and installation restrictions on burial depth, cable spacing, and medium homogeneity can be relaxed. Potential sources of nuisance alarms can easily be located and overcome. The pinpoint location can be used to provide better CCTV assessment, target capture for video motion sensors and more effective response to intrusions. Through the use of parallel cables the sensor can be used to detect the direction of crossing and to classify targets such as small animals, people, and vehicles. This patented next generation of GUIDAR technology represents a dramatic step forward from that which was introduced at the 1976 Carnahan Conference in Lexington, Kentucky, and the numerous CW leaky coaxial cable sensors that evolved from that work. This technology effectively addresses residential, commercial, industrial, and governmental requirements including those relating to homeland security, military operations, and prisons.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 0.016 |
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 source (direct Gemma or distilled Codex), 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".