Fortem Radar

Fortem Radar Experiments

Equipment Specifications

The 15 GHz commercial Fortem TrueView R20 radar. This is an Integrated software defined radar.

The compact all-weather radar can accurately detect a potential target/threat in day or night, in fog, smog or at high

altitudes in the clouds.

Specification and capabilities:

1. Size, Weight, Power and Cost (SWAP-C) electronically scanned phased array radar:

-Size: 200 mm (7.9”) x 75 mm (2.96”) x 38.3 mm (1.5”); Weight: 748 g (1.65 lbs.); Low power: 18‐36V DC

-Built‐in proprietary electronically steered phase array antenna technology

2 .On-board Graphical User Interface (GUI)

3. Programmatic control using API

4. Azimuth field of view (FOV) is 120°; Elevation FOV is 40°

5. Outputs format: range/distance, 2° accuracy, velocity (range rate), and size (radar cross section)

6. Data rate is under 3kHz per intruder with a 8 Hz update rate

7. Ethernet output (JSON) for real-time detection streaming

8. Serial or Ethernet connectors for control and data are alongside a power connector

9. Serial RS‐232 for inputs from GPS or altitude, heading reference data

10.Integrated inertial navigation system (INS) enables clutter rejection in R20 airborne applications

11. Doesn’t disrupt critical RF communications or GPS-dependent equipment

Capabilities:

1. Real-time simultaneous detection, localization, and tracking of multiple objects

2. Detects targets with small RCS (Radar Cross Section) like UAVs and birds. A target with 0.1 m² RCS can be detected at 800 m

3. Detects RF-silent drones

4. Can be distributed and networked to cover any terrain, population center and infrastructure (Fortem SkyDome)

5. Can be mounted on a hunter drone and used to pursue and intercept rogue drone (Fortem DroneHunter)

6. Can use AI or ML at the Edge to identify and assess the threats of all objects.

Case Study: Distinguishing Birds and UAVs

Objective: For Improved detection of unmanned aerial vehicles (UAVs) using a radar, there is a need to characterize the targets of interest. In this study, we use the 15 GHz Fortem radar for target characterization.

Challenge: Beyond detection, it is important to correctly identify radar targets and distinguish them from air clutters like birds which can produce false alarms.

Equipment: The 15 GHz commercial Fortem TrueView R20 radar, PC for data logging,

Targets Types: (A) Harris’s Hawk, and (B) DJI Phantom 4 Pro, (C) DJI Mavic Pro, (D) OWL, (E) DJI Matrice 600, (F) DJI Inspire 1 Pro

Experimental Scenarios:

Although birds and UAVs have similar average RCS, to correctly identify these targets, we have to develop a classification algorithm that exploits the RCS statistics of targets. . In the figure below, we see the RCS statistics of the Harris Hawk and the DJI Inspire are quite different. We can attribute the difference in RCS statistics to the variation in geometric shape (or scattering centers), material properties, frequency, polarization, and even orientation of the targets(azimuth/elevation)