A Low‐Cost FMCW Radar for Perimeter Surveillance With Suppression of Impact of Trees and Bushes as Clutter
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT Radar sensors are one of the most convenient and effective options for perimeter surveillance applications, where a narrow‐beam radar is needed due to the presence of various clutters, particularly trees and bushes, in urban and rural environments. In this paper, an efficient short‐range frequency modulated continuous wave radar is designed and implemented in the X‐band. The radar transceiver and antenna are built on microstrip substrates. A 2D fast Fourier transform algorithm is used to measure the target characteristics. In perimeter surveillance applications, it is challenging and costly to differentiate pedestrians from clutter due to the pedestrians' movement within the radar beam's cross‐section and their similar motion to nearby trees and bushes. In this work, a simple method is employed using two receiving antennas and one transmitting antenna, and a signal processing algorithm to artificially create a fixed beamwidth of less than 1.5 m over a range of 100 m, as opposed to the natural antenna beamwidth that would cover an increasingly larger area as distance from the antenna increases. The achieved fixed beamwidth prevents the detection of clutters such as moving trees in the surrounding area. The entire system is built and tested, confirming a 96%–100% error‐free motion detection.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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