2026-10-10T13:02:36Z https://www.scidb.cn/oai

10.57760/sciencedb.012h5 2026-09-15T11:31:57Z

2026-09-15 Measured Validation Dataset for Credibility Calibration of Multi-Fidelity Radar Plot Data in Equipment Digital Twins (171 Target-CPI Raw Echoes, Flight-Log Truth, and Derived Calibration Products) doi:10.57760/sciencedb.012h5 en This dataset supports the real-data validation (Section 5.11) of the paper "Credibility Calibration of Multi-Fidelity Plot Data Quality for Radar Equipment Digital Twins". Data were collected in an anti-UAV field trial with a Ku-band pulse-Doppler radar (16.3 GHz carrier, 12.5 MHz sampling, 12 MHz waveform bandwidth, 64-pulse coherent integration), observing a cooperative target (DJI Air 3S) on a radial flight segment (azimuth ~142.5° north-referenced, elevation 2°–6°, range 0.5–2.2 km). The dataset contains: (1) raw echo files of 171 target-beam-position CPIs (204,800 bytes each: a 768-byte header plus 64-pulse IQ samples), which constitute the complete raw dependency of the paper's measured results; (2) 10 Hz flight-log truth (latitude/longitude/altitude/velocity), with 21 CPIs truth-aligned to reference plots from the full 64-pulse trusted processing chain, forming real high-fidelity anchors; (3) derived calibration products, including unified plot-quality rows for five sources (full signal-level chain, effect-equivalent probabilistic chain, analytic radar-equation model, and two reduced-integration chains), the five-source calibration summary, theoretical-source parameter calibration, a cross-mechanism consistency report, and a K=100 seed-stability sweep; and (4) preregistration documents (main experiment plan, measured-experiment requirements and instantiation mapping, and nine preregistered expectation checks). The full all-beam-position raw corpus (85,494 CPIs, ~234 GB) is available upon reasonable request subject to approval. Companion code and simulation data are archived in a Gitee repository (https://gitee.com/jiangsu-yunhefeng-intelligent_0/digital-twins-hf-mf-lf). The dataset supports reproduction and benchmarking of radar plot data quality assessment, multi-fidelity data calibration, and data-entry-layer quality management for equipment digital twins. radar; digital twin; plot data; credibility calibration; multi-fidelity data; anti-UAV; pulse-Doppler radar; data quality Hu Wen PUBLIC https://mit-license.org dataset Science Data Bank