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https://github.com/denv3rr/tracer-2


https://github.com/denv3rr/tracer-2

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  ### **Tracer 2**

  

  ![GitHub top language](https://img.shields.io/github/languages/top/denv3rr/Tracer-2)

  ![CMake Min Version Required](https://img.shields.io/badge/cmake_min_vers_req-3.10-green)

  ![GitHub Created At](https://img.shields.io/github/created-at/denv3rr/Tracer-2)

  

  ![GitHub repo size](https://img.shields.io/github/repo-size/denv3rr/Tracer-2)

  ![GitHub last commit (branch)](https://img.shields.io/github/last-commit/denv3rr/Tracer-2/main)

  ![Website](https://img.shields.io/website?url=https%3A%2F%2Fseperet.com)



  


  


    

    


[About](#adaptable) | [Run and Debug](#run-and-debug) | [Issues](#issues) | [Contributing](#contributing) | [Links](#links) | [Contact](#contact)

    


  

    

        











### **Adaptable.**



A **tracking solution** designed for dynamic environments with precision via automated mode-switching - reliability even in the event of a sensor failure or error.



This is (*currently*) a **console application** being built to research movement patterns, Kalman filtering, heat signature detection, and predictive modeling.











    









  

**Building with:**



![C++](https://img.shields.io/badge/c++-%2300599C.svg?style=for-the-badge&logo=c%2B%2B&logoColor=white) ![CMake](https://img.shields.io/badge/CMake-%23008FBA.svg?style=for-the-badge&logo=cmake&logoColor=white)





**Planned Features:**

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  - **Kalman Filtering:** Leverages a few statistical methods for optimal state estimation, ensuring accurate position tracking even in noisy conditions.

   

  - **Heat Signature Detection:** Integrates thermal data to enhance tracking capabilities, enabling the identification of objects based on their heat emissions.

   

  - **Predictive Algorithms:** Employ quick prediction techniques to anticipate movements and improve response times in any potential scenarios.

    

  - **Dead Reckoning Failsafe:** Maintains tracking integrity when GPS or thermal inputs are compromised, ensuring continuous operation through smart estimations of position.

    

  - **Real-Time and Test Modes:** Easily switch between real-time tracking and a comprehensive test mode for simulations and performance evaluations, facilitating robust development and debugging.   



  - **Building with CMake** for modularity and scalability, this application is designed for developers looking to integrate sophisticated tracking capabilities into their projects.



















### **Run and Debug**



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1. **Clone source code or download the `.zip`**



    - Clone: `git clone https://github.com/denv3rr/Tracer-2`

    - `.zip`: https://github.com/denv3rr/Tracer-2/archive/refs/heads/main.zip

   

2. **Build and run** (as of 3/17/2025)

   

    - **To build using CMake:**

  

        - Make sure you have CMake (3.10+): https://cmake.org/cmake/download

        - Navigate to `AirTrace\build`

        - Run cmake: `cmake ..`

        - Build: `cmake --build .`

        - The project is built. 

  

     - **To run from the `Debug` folder:**

  

        - `cd` from `Tracer-2\build` to: `Tracer-2\build\Debug`

        - Run the `Tracer-2.exe` file that you built.



















### **Issues**



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If you have any problems with anything, **submit an issue** to let me know.



[Tracer-2 Issues](https://github.com/denv3rr/Tracer-2/issues)
















### **Contributing**



Expand







Contributions welcome.



You can fix this repo and create a pull request with any changes.



[Create a new fork](https://github.com/denv3rr/Tracer-2/fork)















### **Links**



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- **Seperet** || [Seperet](https://seperet.com) ![Website](https://img.shields.io/website?url=https%3A%2F%2Fseperet.com)  






  

- **Kalman Filter** || [An Introduction to the Kalman Filter - MIT](http://www.mit.edu/~jwilson/kalman.pdf)

- **Understanding Kalman Filters** || [An Introduction to the Kalman Filter - University of North Carolina](https://www.cs.unc.edu/~welch/media/pdf/kalman_intro.pdf)

- **Tutorial: The Kalman Filter** || [Tutorial: The Kalman Filter - MIT](https://web.mit.edu/kirtley/kirtley/binlustuff/literature/control/Kalman%20filter.pdf)

- **Predictive Algorithms in Motion Tracking** || [An Elementary Introduction to Kalman Filtering - University of Texas](https://www.cs.utexas.edu/~mooney/cs343/kalman.pdf)

- **Thermal Detection** || [Long-Range Thermal Target Detection in Data-Limited Settings Using Restricted Receptive Fields](https://www.mdpi.com/1424-8220/23/18/7806) 

- **Detecting Minimal Thermal Signatures** || [Detecting Small Size and Minimal Thermal Signature Targets in Infrared Imagery Using Biologically Inspired Vision](https://www.mdpi.com/1424-8220/21/5/1812)


















### **Contact**




  

  


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