<![CDATA[Accurate localization of base transceiver stations (BTS) remains challenging because radio-signal propagation varies with distance, buildings, vegetation, multipath, and non-line-of-sight conditions, while reports of a replicable end-to-end workflow linking SDR signal acquisition, cell-identity extraction, and location matching remain limited. This study aims to evaluate the feasibility of a low-cost RTL-SDR-based fingerprinting workflow for detecting BTS across five environment types, comparing DragonOS performance with a comparison system, and assessing the resulting location estimates. The study used a field-experiment design with descriptive analysis across five environments in Karawang: campus, residential, office, dense-building, and open areas. The fingerprint consisted of MCC, MNC, LAC, Cell ID, ARFCN, and RSSI extracted using RTL-SDR, DragonOS, GR-GSM, GQRX, and Wireshark, then matched against a cell-location API. Data were analyzed descriptively using detection rate, mean RSSI, scan time, system-resource use, and Pearson correlation. Of 63 reference BTS, 56 were detected (88.9%), with detection ranging from 70.0% in the dense-building area to 100% in the open area and mean RSSI from -74 to -45 dBm (SD = 11.1 dBm). DragonOS detected 13 BTS in 23 seconds with lower CPU and memory use than the comparison system, which detected 9 BTS in 41 seconds. The location lookup returned coordinates -6.357825, 107.370934 with an estimated radius of 900 m, indicating the workflow is feasible for preliminary BTS identification, though it does not yet establish classic fingerprinting positional accuracy.]]>
