ATAKRR (Android Team Awareness Kit Radio Reconnaissance) is an ATAK plugin designed for hands-free EW recon by warfighters in the field. It provides EWW (Electronic Warfare for the Warfighter). It’s designed to function in the background, gathering information without interaction for later SIGINT analysis. It also provides an interactive real-time interface that allows warfighters to assess their surrounding RF environment and attempts to geolocate transmission sources and identify them using AI, presenting them in an easy-to-understand format to the operator.

📡 ATAKRR: Android Team Awareness Kit – Radio Reconnaissance Plugin

🎯 Project Overview

ATAKRR (Android Team Awareness Kit: Radio Reconnaissance) is a lightweight, field-deployable plugin for the Android Team Awareness Kit (ATAK) that provides real-time radio frequency (RF) signal awareness, direction estimation, and tactical signal intelligence capabilities. Built with mobility, resilience, and human-in-the-loop adaptability in mind, ATAKRR empowers teams to operate effectively in contested or denied RF environments without relying on centralized infrastructure.

🧭 Core Capabilities

✅ Signal Discovery & Classification

• Scans ambient RF spectrum using Software Defined Radios (SDRs)
• Uses onboard AI/ML models to classify observed signals (Wi-Fi, Bluetooth, LoRa, etc.)
• Signals are sorted by strength, with team-known signals optionally exempted from display
• Sub-categorization available by band, protocol, or operational type

📍 Direction Estimation

• Estimates direction of signal sources using motion-based vector tracking (single device)
• Optionally enables triangulation across multiple networked devices for greater accuracy
• When direction is detected, renders a gradient overlay in the estimated direction of origin
• Shows signal type and estimated confidence using Bayesian probability scoring

🛰️ Communication & Decentralization

• Supports peer-to-peer communication between team members via ATAK networking layer
• Built on a fog computing architecture:
  • Each device functions independently
  • Optionally links to a backpack-class edge node (e.g., mobile server or HMMWV-mounted)
  • Edge nodes can optionally sync with cloud infrastructure for post-op analysis or remote access
  • All systems fail gracefully: cloud optional, team network optional, fallback to local-only