1. Introduction

In modern battlefield operations, speed and accuracy in communication are paramount. Joint Terminal Attack Controllers (JTACs), UAV operators, and ground force commanders rely on real-time information to make mission-critical decisions. Traditionally, these commands require manual data entry, which leads to delays, human errors, and cognitive overload.

This project introduces a real-time voice command system that converts spoken battlefield commands into Cursor-on-Target (COT) messages. These messages can be directly transmitted to Tactical Assault Kit (TAK) applications (ATAK, WinTAK, etc.), improving situational awareness, reducing workload, and increasing operational efficiency.

2. Project Goals

✅ Enable hands-free, real-time battlefield command input using voice recognition.

✅ Accurately transcribe and parse military commands (e.g., airstrikes, reconnaissance, target tracking).

✅ Generate COT messages from voice commands and transmit them to TAK servers.

✅ Ensure low-latency processing (<1 sec response time) and offline functionality for disconnected environments.

✅ Multi-user support: Allow JTACs, UAV pilots, and ground teams to interact via voice input.

✅ Compatibility with existing TAK networks, radios, and mobile devices.

✅ Robust keyword and command detection to recognize various mission-critical phrases and synonyms.

3. Use Case Scenarios

This system is designed to support various military operations, including airstrikes, reconnaissance, friendly tracking, and UAV coordination.

3.1 JTAC Close Air Support (CAS) Request

• Command: “Request airstrike on enemy armor at grid 38T MM 1234 5678.”
• System Response:
  • Extracts command type ("Request Airstrike"), target type ("enemy armor"), and coordinates ("38T MM 1234 5678").
  • Generates COT message and sends to TAK for immediate execution.

3.2 UAV Operator Target Tracking

• Command: “Track vehicle at latitude 34.789, longitude -118.456.”
• System Response:
  • Recognizes tracking command and extracts coordinates.
  • Creates real-time tracking marker in TAK and continuously updates it.

3.3 Recon Team Reporting Friendly Position

• Command: “Friendly forces holding position at grid 43S XR 2345 6789.”
• System Response:
  • Identifies unit type ("Friendly Forces"), status ("holding position"), and coordinates.
  • Generates a blue force tracking COT marker for command HQ.

3.4 Suppression Fire Request

• Command: “Suppress enemy infantry at grid 16R CT 4567 1234.”
• System Response:
  • Extracts command type ("Suppress"), target type ("enemy infantry"), and coordinates.
  • Generates a suppression COT marker.

4. System Architecture

4.1 Core Components

Component Function Speech Recognition Module Converts battlefield voice commands to text RealtimeSTT Natural Language Processing (NLP) Extracts key elements (command type, entity, coordinates) using spaCy/NLTK. COT Message Generator Converts extracted data into COT XML format. COT Transmission Module Sends COT messages via UDP, TAK Server, or direct ATAK API integration. GUI / Debug Console Displays live transcriptions, parsed commands, and COT messages.

5. Technologies & Tools

Component Technology Used Speech Recognition RealtimesSTT Natural Language Processing (NLP) spaCy, NLTK, Regex-Based Extractors COT Message Handling Python (ElementTree, lxml for XML parsing) Backend API FastAPI, Flask Transmission UDP, TAK Server, Radio Network Hardware Support Raspberry Pi, NVIDIA Jetson, Mobile Devices

6. Challenges & Considerations

🔴 Accuracy in Noisy Environments: Battlefield conditions include radio distortion & background noise.

🔴 Processing Speed: Commands must be processed in real-time (<1 second latency).

🔴 Security: COT messages must be encrypted for secure transmission.

🔴 Deployment on Edge Devices: Optimizing models for low-power military devices (Raspberry Pi, Jetson).

🔴 Multi-Modal Integration: Potential for gesture-based control or touch-screen fallback.

🔴 Handling Variability in Speech: System must recognize synonyms, accents, and military jargon.

7. Project Achievements

🚀 Successfully developed a prototype that converts voice commands into real-time COT messages.

🚀 Achieved seamless integration with TAK (ATAK, WinTAK, etc.).

🚀 Enabled offline processing with local speech-to-text models.

🚀 Built a GUI with live transcription and debugging logs.

🚀 Improved keyword detection for commands and targets using NLP techniques.

🚀 Implemented COT message transmission via UDP for real-time battlefield integration.