Dedrone is an RF-first airspace-security platform, and its own material is refreshingly direct about it. Dedrone states that “the DedroneSensors RF-160 and RF-360 radio frequency sensors detect and locate drones based on their individual radio signals”, describes the RF-360 and RF-360T as “passive, network-attached radio sensors for the detection, classification, and localization (geolocation) of drones and their remote controls”, and positions PTZ cameras and radar as additions: radar systems, in Dedrone’s words, “are used to supplement the RF sensors”. RF is the primary sensor. Everything else is cued by it or added to it.
GOTEAM inverts that order. The imaging sensor is the primary detector, not the confirmation step. A fixed, wide-field uncooled thermal node images the entire scene on every frame and searches all of it with an on-edge neural network, so there is no cue to wait for and no sector that is unwatched while the sensor is looking somewhere else. Range, bearing and elevation come out of the same track that produced the picture.
The consequence is a clean split in what each architecture can miss. An RF-cued system misses the drone that never transmits — fibre-optic-controlled, pre-programmed, fully autonomous — because there is nothing to cue on. A thermal imager misses the drone it cannot see: behind a building, over a ridge, inside dense fog. Neither of those is a bug. They are the two techniques doing exactly what they are.
Where a Dedrone capability is quoted below it comes from Dedrone’s own published material; where it is not, the row is written at the level of the technique — passive RF sensing versus passive thermal imaging — which is true by physics and needs no vendor citation. See the note at the foot of the page.
One property generates most of this table: the detector needs no cue. Because the whole field of view is imaged and searched every frame, a target that emits nothing, is unknown to any library, and is doing nothing a radio would reveal is still simply a warm object moving through the sky.
| Capability | GOTEAM | RF-cued detection |
|---|---|---|
| Detects a drone that emits no radio signal at all | ✓heat and shape, not a link | ◐Dedrone RF sensors ✗ — they “detect and locate drones based on their individual radio signals”; ◐ with Dedrone radar/PTZ extensions: “Radar Surveillance even Detects Autonomous Drones”, and “DedroneTracker.AI software has an intelligent video analysis capability, which detects and locates drones in real-time” |
| No cue needed to point a sensor — the whole field of view is searched every frame | ✓fixed stare, no gimbal, no blind time | ◐RF sensors watch continuously; the camera that produces the picture is steered to what RF found |
| Detection independent of a drone-signature database staying current | ✓an unfamiliar airframe is still a warm object | ✗RF classification works against a library of known drone radio properties |
| Multi-target and swarm handled natively, at the same latency per target | ✓“one drone or twenty, at the same latency” — no camera to share between targets | ◐a single steerable camera can point at only one target region at a time |
| Bird-versus-drone discrimination from the imagery itself | ✓neural classification plus flight-behaviour cues that down-weight birds | ◐Dedrone RF sensors ✗ — birds do not transmit, so the RF layer does not answer it; ◐ with Dedrone radar/PTZ extensions, where DedroneTracker.AI’s “intelligent video analysis capability” classifies from the camera picture |
| Full detection chain runs on the node with no cloud and no uplink | ✓offline-capable; needs only power and a field of view; store-and-forward when the link drops | ◐Dedrone markets “fast installation and start-up due to cloud-readyness thanks to integrated LTE and GPS”; offline operation is not documented at this level |
| No mechanical wear items in the detection path | ✓no gimbal motors, slip rings or cryocooler | ◐the RF sensor has none either; the PTZ camera that confirms the target does |
| SAPIENT / BSI Flex 335 v2 detection reports to third-party C2 | ✓hub is a SAPIENT server and client | —DedroneTracker.AI is the published platform; SAPIENT conformance not stated in the material reviewed |
| Detection engine licensable as software onto a third party’s thermal core | ✓camera-agnostic; Jetson or x86 with Intel Arc | — |
Both products detect drones passively, classify them, put them on a map and hand the result to an operator. The mark would be a tick in both columns and would tell you nothing. Read the cells.
| GOTEAM does it by… | Dedrone does it by… | |
|---|---|---|
| Operating without emitting | Passive EO/IR. No radar pulses, no RF, no spectrum licence anywhere, nothing for an adversary to direction-find. | A passive radio receiver. The RF-360 and RF-360T are described as “passive, network-attached radio sensors”, and Dedrone notes the product requires “no legal authorization”. |
| Detecting the drone | Imaging it. Sixteen-bit thermal frames, sky and cloud suppression, a neural detector trained on tens of thousands of hand-verified thermal drone frames, then a tracker that confirms only what persists and moves consistently. | Hearing its radio. Detection, classification and geolocation from the drone’s and controller’s signals, in a receiver Dedrone describes as “optimized for RF noisy environments”. |
| Producing a picture of the target | The detection is the picture. The thermal frame that triggered the track is the evidence: an annotated clip and zoom-crop thumbnails, reviewable afterwards and reprocessable against newer models from the node-side raw frame archive. | A steered camera. Dedrone: “PTZ cameras have a Pan, Tilt, and Zoom function. Thanks to the powerful zoom, even small drones can be detected at great distances.” Far more pixels on target than a wide-field sensor — once something has told it where to look. |
| Putting it on a map | Range, bearing and elevation per confirmed track, with a positional-uncertainty ellipse, on a live tactical map across web, iOS and an installable PWA — and out to third-party C2 over SAPIENT. | RF geolocation. Dedrone: “RF-based localization finds drones and pilots and plots them on a map” — two objects on the map where GOTEAM can only ever plot one. |
| Adding a second modality | Fusing outward. GOTEAM is explicitly a layer: it cross-cues RF, acoustic and radar sensors through an open API and SAPIENT rather than absorbing them. | Adding sensors around RF. Cameras for visual confirmation and, where required, radar — which Dedrone says “are used to supplement the RF sensors”. |
Where GOTEAM is stronger. Nothing has to happen for GOTEAM to detect. No transmission, no cue, no slew, no library entry. That matters precisely for the threat profile the market is moving toward — fibre-tethered FPV, pre-programmed routes, autonomy — where every one of the things an RF-first architecture depends on has been deliberately removed by the attacker. It matters again against a swarm, where a single steerable camera has to choose which target it is looking at and a fixed sensor does not.
Where Dedrone is stronger. Reach, robustness to weather and obstruction, and the operator. A five-kilometre direction-finding envelope from one sensor is an order of magnitude beyond what GOTEAM publishes for optical detection; it works when the sky is white and when the drone is behind a hangar; and it finds the person flying the aircraft, which for a police, prison or airport customer is frequently the entire point. Add a zoom camera and you get identification detail at a range no wide-field sensor can match.
Use both. This is not diplomacy — it is GOTEAM’s published position, which states that GOTEAM complements RF and acoustic sensors rather than replacing them and fuses with them through an open API. The failure modes are close to disjoint: RF loses the silent drone, thermal loses the obscured one. Running RF for reach and operator location, with a passive thermal layer covering the cases that generate no signal, removes the single largest blind spot in each.
Dedrone capabilities and all quoted phrases on this page are taken from Dedrone’s own published material as of September 2026 — dedrone.com, its counter-drone technology page, its RF-360 sensor page and its radar and PTZ-camera extension pages. Last reviewed: October 2026. ◐ = partial — present but narrower than the other column, or true of one part of the architecture and not another. — = not documented publicly: a capability Dedrone’s published material does not address at this level of detail, not a claim that it is absent. GOTEAM marks reflect capability published on this site and in /llms.txt; specifications beyond that are shared under NDA after vetting. Rows written at the level of the technique — that a radio receiver needs a transmitter, that an imager needs line of sight — are properties of the physics and apply to every product of that class, GOTEAM’s included. Dedrone, DedroneSensors and DedroneTracker are trademarks of their respective owner; this is an independent capability comparison, not an endorsement, and every product here evolves — verify specifics against current documentation.
Upload a thermal or EO clip to FlyBox and a GOTEAM field device processes it on real hardware, streaming back an annotated result with per-frame detections and range and bearing.