Shen-kl/MCST
Official implementation of paper "MCST: An adaptive tracking algorithm for high-speed and highly maneuverable targets based on bidirectional LSTM network"
This project helps defense or aerospace professionals accurately track high-speed, highly maneuverable objects like hypersonic missiles or advanced aircraft using radar data. It takes in raw radar measurements of an object's position and outputs precise estimates of its real-time location and velocity, along with an understanding of how uncertain those estimates are. This is for radar engineers, systems integrators, or defense analysts who need to improve the reliability of target tracking systems.
Use this if you need to reliably track fast-moving, unpredictably maneuvering targets, especially in situations with noisy radar observations or when targets might temporarily disappear from detection.
Not ideal if you are tracking slow-moving, predictable targets, or if your primary concern is tracking stationary objects or ground vehicles.
Stars
12
Forks
1
Language
Python
License
—
Category
Last pushed
Oct 31, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/Shen-kl/MCST"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
DeepTrackAI/DeepTrack2
DeepTrack2 is a modular Python library for generating, manipulating, and analyzing image data...
abhineet123/Deep-Learning-for-Tracking-and-Detection
Collection of papers, datasets, code and other resources for object tracking and detection using...
NVIDIA-ISAAC-ROS/isaac_ros_dnn_inference
NVIDIA-accelerated DNN model inference ROS 2 packages using NVIDIA Triton/TensorRT for both...
DagnyT/hardnet
Hardnet descriptor model - "Working hard to know your neighbor's margins: Local descriptor...
imatge-upc/detection-2016-nipsws
Hierarchical Object Detection with Deep Reinforcement Learning