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Russian Rosel passive coherent radar detects UAVs without emission

Bottom line

Rostec subsidiary Rosel presents the 3D PKL, a passive coherent radar that detects small UAVs using reflected TV and radio signals, claiming immunity to enemy EW and anti-radiation missiles.

Why it matters

Passive coherent radar technology offers a potential countermeasure to GPS-denied or EW-heavy environments, allowing Russian air defense to detect low-observable drones without revealing their position to enemy targeting systems.

Rostec’s Rosel subsidiary has presented the 3D PKL, a passive coherent radar system designed to detect small UAVs by analyzing reflected TV and radio signals rather than emitting its own radar pulses. The system uses Doppler shift for tracking and claims to be invisible to enemy electronic warfare and anti-radiation missiles, addressing the vulnerability of active radar systems in modern drone warfare.

Evidence — 1 independent origin

  • Ростех (Rostec)source Dorigin t.mearchive
    Original text (excerpt)

    📡 3D ПКЛ закрывает слепую зону в защите инфраструктуры. Трехкоординатный пассивный когерентный локатор 3D ПКЛ разработки нашего холдинга Росэл способен выявлять малоразмерные БПЛА без использования собственного передатчика. Технология делает комплекс практически невидимым для сре

NamedRostec3D PKLRoselTopicsdroneselectronic warfarecomponentsrussia

Related findings

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History · version 1 · first published · last substantive update

Cite this finding
Robot War (2026). Russian Rosel passive coherent radar detects UAVs without emission. Hetzner OSINT, 8 October 2026. https://robotwar.io/osint-hetzner/2026-10-08--russian-rosel-passive-coherent-radar-detects-uavs-without-emission/

@misc{robotwar-2026-10-08--russian-rosel-passive-coherent-radar-detects-uavs-without-emission,
  title = {Russian Rosel passive coherent radar detects UAVs without emission},
  author = {Robot War},
  howpublished = {\url{https://robotwar.io/osint-hetzner/2026-10-08--russian-rosel-passive-coherent-radar-detects-uavs-without-emission/}},
  year = {2026},
  note = {Hetzner OSINT finding D4}
}

Grades: source reliability A–F from the channel register; information credibility 1–6 from independent origins — reposts count once. The bottom line and summary are written by the model from the cited posts; grades and source roles are rule-based. Methodology 2026-10-15.v6 · Corrections · JSON · RSS · API performance