drone-detection

Multi-protocol SDR signal detection and triangulation system for ATAK. Detects radio emissions from distributed receivers using RTL-SDR and HackRF.

🔇 A production-grade deep learning system for real-time drone/UAV detection through acoustic signature analysis. Converts raw audio to Mel-Spectrograms and classifies using a custom CNN. Features auto-dataset ingestion, defense-optimized metrics (high recall), early stopping, model checkpointing, and a ready-to-use inference API.

TIB-Net: Drone Detection Network With Tiny Iterative Backbone

This project provides a trained YOLOv8 model for detecting both multirotor and fixed-wing UAVs (drones) in visual data. Includes example usage and documentation.

Një model për ti detektuar dronat nga imazhet, videot dhe regjistrimet në kohë reale duke përdorur YOLOv3 dhe PyTorch.

Real-time RF signal intelligence pipeline for drone RF classification, live SDR replay/receive, ONNX export, TensorRT deployment on NVIDIA Jetson, and Nsight-profiled edge inference.

Local web console for WarDragon drone detection kits — health dashboard, curated DragonSync config editor, USB-tether tablet access

From dataset https://universe.roboflow.com/drone-detection-pexej/drone-detection-data-set-yolov7/dataset/1 a model is obtained, based on yolov10 to detect drones in images. Predictions from several models are used in cascade to obtain the optimal result.

This project is a Python-based GPS spoofing detection tool designed to analyze and detect anomalies in GPS data, which is a crucial step toward defending against malicious interference with Unmanned Aerial Systems (UAS). Initially built for dataset-based detection, this tool will evolve into a specialized weapon in the COUNTER-UAS (C-UAS) arsenal

Drone YOLO Object Detection 📦🛩️ This repository contains a full pipeline for training a YOLOv8 model on custom drone footage data for object detection and line-crossing analysis. The implementation uses the Ultralytics YOLOv8 framework and is tailored for lightweight and fast inference using the YOLOv8 Nano variant.

Lightweight YOLOv8-based UAV detection pipeline for long-range small-target detection, optimized for edge-compatible deployment and evaluated on the DUT-Anti-UAV dataset.

AIegis Beam (formerly known as Mini C-RAM (Counter Rocket, Artillery & Mortar)), the real-time drone detection/tracking system (university capstone project).

The app is designed for drone signal detection, spectrum analysis, and experimental jamming using HackRF. False positives are possible, but the program attempts to analyze signals based on many drone-specific parameters.

Since have been noticed that Roboflow's RFDETRBase incorporates the drone class as an additional class, this drone detection program is presented.

Landmine Detection using Drone Camera is an AI-powered drone project designed to enhance safety in mine-affected areas. The system uses a drone equipped with a camera and computer vision algorithms to detect landmines in real-time, allowing operators to safely monitor and avoid hazardous zones.

See the drone, then hit it — finding a 3-14 pixel drone in 720p video from a moving camera, then closing on it with camera-only proportional-navigation guidance. Detection measured on real video; interception closed-loop in Isaac Sim.

Estimate a drone operator's location from ground-position sightings via Monte-Carlo viewshed intersection on real terrain.

Drone RFML Research Hub — RF-based drone detection, classification & tracking using MoE architectures

Drone Project Using Q-Learning : Helping a Drone find a target. Core framework is made to be used with Tello drones, so this algorithm may be compatible with them.