Unmanned
Systems
Tracker
Open-source database tracking drone warfare, USV strikes, UGV operations, and Russian losses in Ukraine.
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| Date ↕ | Target ↕ | Type | USV Model ↕ | Location | Damage ↕ | Notes | Source |
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| Date ↕ | Side ↕ | UGV System ↕ | Operation / Target | Location | Outcome ↕ | Notes | Source |
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| Date | System / Target | Type | Location | Outcome | Source |
|---|---|---|---|---|---|
| Aug 2025 | GLONASS relay + RT-70 telescope | Strategic comms / SIGINT | Yevpatoriya, Crimea | Destroyed | tochnyi.info · 31st Air Defence Division HQ complex |
| Sep 10, 2025 | 40th Command & Measurement Complex HQ | C2 / deep space comms | Yevpatoriya, Crimea | Destroyed | tochnyi.info · HQ building + main comms building struck |
| Sep–Feb 2025/26 | 55Zh6U Nebo-U radar (×4 strikes) | VHF early-warning radar | NW Yevpatoriya, Crimea | Repeatedly hit | tochnyi.info · Same position struck at least 4 times |
| Jul 2025 | S-350 Vityaz SAM system | Medium/long-range SAM | Occupied Ukraine | Destroyed | tochnyi.info · 1 of 3 confirmed S-350 strikes (Jul–Feb) |
| Nov 2025 | S-350 Vityaz SAM systems (×7) | Medium/long-range SAM | Occupied Ukraine | Destroyed | tochnyi.info · Peak month — 7 strikes in single month |
| Mar 9, 2026 | 5N84A Oborona-14 radar | Long-range early warning | Crimea | Destroyed | United24 Media ↗ · SSO drone strike |
| Mar 9, 2026 | 55Zh6U Nebo-U radar (×2 in radomes) | VHF early-warning radar | Yevpatoriya, Crimea | Destroyed | United24 Media ↗ · 4 radar systems in single operation |
| Mar 22, 2026 | S-400 SAM system radar | Long-range SAM | Occupied Donetsk Oblast | Destroyed | ISW Mar 22 ↗ · USF strike, Brovdi confirmed |
| Mar 1–22, 2026 | Russian air defence equipment (×26) | Mixed SAM/radar | Operational depth | 26 systems | ISW Mar 22 ↗ · USF Commander Brovdi statement |
| Mar 2026 | 40th C&M Complex HQ (re-strike) | C2 / deep space comms | Yevpatoriya, Crimea | Re-struck | tochnyi.info · Second strike on same complex |
Independent Russian media outlet maintaining the most rigorous publicly available list of Russian soldiers killed — confirmed by name using obituaries, social media, and official sources. Cross-checked against the National Probate Registry. This tracker uses Mediazona/BBC as its primary KIA source.
en.zona.media ↗Independent Russian investigative outlet. Works with Mediazona to produce statistical estimates of total Russian deaths using probate registry excess mortality data — giving a broader picture beyond what's confirmed by name. Estimated ~352,000 killed to end of 2025.
meduza.io ↗The gold standard for equipment loss tracking — every entry in the Oryx database is individually photo or video confirmed. Tracks Russian and Ukrainian losses of tanks, AFVs, aircraft, and naval vessels. Ceased updating in 2025 but the historical record remains essential.
oryxspioenkop.com ↗The most detailed open-source technical analysis of Ukrainian and Russian USVs. H.I. Sutton documents every known drone boat variant with specifications, operational history, and imagery. Essential reference for USV platform identification and capabilities.
hisutton.com ↗Consistently the best English-language specialist defence reporting on USV and UGV developments. Well-sourced, sceptical of unverified claims, and fast to cover new platform developments. Used extensively as a secondary verification source for this tracker.
twz.com ↗Ukrainian-language defence publication with strong English coverage of weapons systems, unmanned platforms and battlefield technology. Particularly valuable for early reporting on new Ukrainian drone and UGV developments, often sourced directly from manufacturers and the Ministry of Defence.
militarnyi.com ↗Ukrainian data scientist maintaining the most comprehensive structured dataset of Russian drone and missile attacks on Ukraine, compiled daily from official Ukrainian Air Force reports. Verified by CSIS as matching official figures. Covers every attack wave from October 2022 to present — the primary data source for the Air Defence tab on this tracker.
github.com/PetroIvaniuk ↗Ukrainian open-source research publication producing detailed long-form analysis of Ukraine's strike campaigns against Russian military assets. Primary source for the Air Defence Attrition section in this tracker — their March 2026 investigation documents Ukraine's systematic campaign against Russian SAM systems and radar networks across Crimea and occupied territories from 2025 onwards.
tochnyi.info ↗The most accurate live frontline map of the conflict. Updated continuously from visual evidence and geolocated footage.
deepstatemap.live ↗Crowdsourced initiative geolocating strikes, troop movements, and infrastructure damage. Each entry individually verified.
geoconfirmed.azurewebsites.net ↗Centre for Information Resilience project tracking and verifying attacks. Strong on civilian harm documentation.
eyesonrussia.org ↗Daily battlefield updates with map assessments. Widely cited by Western governments. Cross-reference with other sources.
understandingwar.org ↗The story of how a school dropout built the world's most influential open-source intelligence unit — and how citizen journalists are redefining the way we think about news, accountability, and the digital future. Essential reading for anyone using this tracker.
Buy on Amazon UK ↗A concise, rigorous guide to war in the contemporary world by a Senior Lecturer in War Studies at King's College London. Examines how technology — including unmanned systems — is transforming warfare and widening the gap between military practice and international law.
Buy on Amazon UK ↗By RUSI's Senior Research Fellow for Land Warfare, who has worked extensively with Ukrainian Armed Forces during Russia's invasion. An authoritative analysis of how autonomous weapons, AI and novel technologies are reshaping the battlefield — the closest thing to a field manual for understanding this tracker's subject matter.
Buy on Amazon UK ↗The definitive history of the conflict by Harvard's foremost Ukraine scholar. Traces the origins of the invasion from the collapse of the Russian empire to the present day — essential context for this tracker's data.
Buy on Amazon UK ↗The first book of frontline reportage from the Ukraine war, by the Guardian's award-winning correspondent. A compelling, on-the-ground chronicle of Russia's invasion and Ukraine's fight for survival.
Buy on Amazon UK ↗Pulitzer Prize-winner Anne Applebaum's devastating account of Stalin's deliberate starvation of Ukraine in 1932–33. Essential background to understanding the deep roots of Ukrainian national identity and resistance.
Buy on Amazon UK ↗The Ukraine War Unmanned Systems Tracker is an independent open-source research project built and maintained by Andro Mathewson, PhD Candidate in War Studies at King's College London. It documents the confirmed and claimed combat use of unmanned systems — surface, ground, and air — in the Russian invasion of Ukraine.
The tracker is built from publicly available OSINT, official Ukrainian military releases, and verified reporting. All entries carry source citations for independent verification. It is maintained alongside ongoing PhD research and updated regularly.
This tracker is not affiliated with any government, military organisation, or commercial entity. It is not affiliated with any of the organisations listed as sources above. Links are provided for research and verification purposes only.
Andro Mathewson
PhD Candidate in War Studies
King's College London
For research collaboration, media enquiries, data requests, or corrections to entries, please get in touch.
Corrections policy
If you believe an entry contains a factual error — wrong date, misattributed source, incorrect damage assessment — please get in touch with the relevant entry, your evidence, and a suggested correction. All corrections are reviewed and applied promptly. Significant corrections are noted on the relevant entry.
Media enquiries
Available for comment on drone warfare, unmanned systems, and the Russia-Ukraine conflict. Data requests, research collaboration, and citation queries welcome.
Cross-referencing 603 Shahed/Geran attack days with night-time weather conditions from the Open-Meteo Historical Archive API. Each attack day was classified as Clear, Overcast, or Adverse based on cloud cover and precipitation.
Clear nights: 70.7% (n=110) · Overcast: 72.2% (n=193) · Adverse: 68.2% (n=300). The 4-point range across conditions is not statistically significant — Ukraine's interception rate is weather-robust.
OLS regression of night-time cloud cover against interception rate shows a near-zero relationship. Cloud cover explains less than 0.3% of variance in intercept outcomes.
Launch volumes are highest on clear nights (150.4/day) vs adverse nights (129.6/day). There is no evidence Russia times swarms to exploit poor weather conditions.
▸ METHODOLOGY NOTE
Weather retrieved for Kyiv (50.45°N, 30.52°E). Night-time = 20:00–06:00 local. Attacks with <10 Shaheds excluded. Clear = cloud cover <30%, Overcast = 30–79%, Adverse = ≥80% or precipitation present.
Tests whether Ukrainian air defence degrades under high launch volumes — identifying the saturation threshold above which interception rates fall. Attack nights are bucketed by total weapons launched across nine volume bands.
The only volume band that consistently falls below the 74% overall mean. Medium-intensity attacks — not mass salvos — are most effective at degrading performance.
At the highest attack volumes (n=10), interception recovers to 83% — above the overall mean. Mass swarms do not overwhelm Ukrainian air defence in the way commonly assumed.
The volume-to-interception relationship is non-linear. No attack nights fell into the overwhelmed category (<55%). The system appears structurally robust at both low and very high volumes.
▸ METHODOLOGY NOTE
Volume buckets: 1–30, 31–60, 61–100, 101–150, 151–200, 201–300, 301–400, 401–600, 600+. Classification: ≥70% = manageable, 55–69% = degraded, <55% = overwhelmed.
A widely cited claim holds that Russia uses Shaheds as decoys to saturate Ukrainian air defence and enable missile penetration. If true, mixed salvos (Shahed + missile) should produce lower overall interception rates than Shahed-only attacks.
Mixed salvos (Shahed + missile, n=497) produce a 73% interception rate vs 75% for Shahed-only (n=411). The 2-point difference is within error margins — mixed salvos do not measurably degrade overall interception.
Missile-only salvos (n=82) produce the highest interception rate at 80%, suggesting Ukraine's missile defence performs well independently of Shahed saturation.
Mixed nights use the highest mean volumes (113 weapons/night vs 101 Shahed-only). Any marginal degradation in mixed salvos likely reflects volume effects rather than a decoy function.
▸ METHODOLOGY NOTE
Salvo types classified from model field: Shahed Only (n=411), Mixed Shahed + Missile (n=497), Missile Only (n=82), Other/Unknown (n=70). Error bars represent 95% confidence intervals.
Tracks the composition of Russian aerial strikes over the full campaign — examining how the balance between Shaheds, missiles, and other UAVs has shifted since August 2022. Both absolute volume and proportional share are examined.
Up from roughly 45–50% in late 2022. The campaign has become a drone-dominant operation, with missiles representing under 10% of launches proportionally by 2025–2026.
Approximately 20× the 2022 baseline. This represents both substitution away from expensive missiles and a raw expansion of strike capacity enabled by Iranian-origin drone supply chains.
Absolute missile numbers remain significant, but their proportional role has clearly shifted — from strategic primary weapon to supplementary precision element within Shahed-dominant salvos.
▸ METHODOLOGY NOTE
Weapon types classified by keyword matching on model field: SHAHED (Shahed-136, Geran variants), MISSILE (Kalibr, Iskander, Kh-series, Kinzhal, Zircon), OTHER_UAV, OTHER. Monthly aggregation.
Tracks how many Ukrainian oblasts are affected per attack over time. Higher values indicate Russia is spreading strikes across more regions simultaneously — with implications for how Ukraine must allocate air defence resources nationally.
After falling to a low of ~3 oblasts per attack in mid-2025, geographic reach tripled to 8+ by March 2026 — a significant shift in Russia's targeting strategy.
Kharkiv (~128) and Sumy (~115) lead by a significant margin, reflecting front-line proximity. Kyiv (~96) and Dnipropetrovsk (~98) follow as primary strategic targets.
Forcing Ukraine to maintain air defence coverage across 8+ oblasts simultaneously creates resourcing pressure that mass volume attacks on a single axis do not — a potential strategic adaptation.
▸ METHODOLOGY NOTE
Geographic dispersion = mean distinct oblasts per attack day, extracted from regions field. 3-month rolling mean applied. Oblast frequency covers full campaign period.
Russia's Rubikon drone unit has published target breakdown statistics across 24,000+ engagements, enabling the first direct comparison of Russian and Ukrainian FPV targeting doctrine. The contrast is striking — and has prompted concern among Russian warbloggers about doctrinal mismatch.
36.7% drone-on-drone (UAVs and ground robots) · 16.7% communications and surveillance equipment · 15.8% fortifications · 12.2% unarmoured vehicles · 8.7% armoured vehicles · 6.6% personnel outside shelters · 2.1% artillery · 0.3% infrastructure
22–30% personnel across reported periods — July 2025: 21.9% (5,134 of 23,433 targets), first half April 2026: 24.2% (4,840 of 20,022), Jun 2025–Jan 2026: 29.9% (50,238 of 168,000+). USF commander Madyar has stated a minimum 30% personnel targeting mandate.
Ukraine prioritises personnel destruction (~25–30% of targets); Russia prioritises materiel and counter-drone (~37% drone-on-drone, only 6% personnel). Russian warbloggers have flagged this as alarming given the economics of war — infantry takes years to produce, vehicles can be factory-built. As of early 2026, unmanned systems account for approximately 60% of all effective strikes on Ukrainian forces.
▸ SOURCE NOTE
Russian data sourced from Rubikon's official Telegram channel via Boris Rozhin (Colonelcassad) and Veterans Notes Telegram commentary. Rozhin is a pro-Russian analyst — figures are taken as reported, framing is independent. Ukrainian data from official USF Pidrakhuyka statistics. Rubikon represents one Russian drone unit, not the full Russian USF equivalent; aggregate Russian figures may differ. Thread compiled by @ChrisO_wiki (independent military history researcher).