3lips/README.md

# 3lips

Target localisation for multi-static radar using ellipse intersections. Not a dating app.

See a live instance at [http://3lips.30hours.dev](http://3lips.30hours.dev).

![3lips example display](./example.png "3lips")

## Features

- Provides a JSON API for geolocation of targets given [blah2](http://github.com/30hours/blah2) radar nodes.
- Uses a [CesiumJS](http://github.com/CesiumGS/cesium) web front-end to visualise data.
- Ability to compare a number of algorithms for target localisation.

## Usage

- Install docker and docker-compose on the host machine.
- Clone this repository to some directory.
- Edit the [./config/config.yml](config./config.yml) file for scenario.
- Run the docker compose command.

```bash
sudo git clone http://github.com/30hours/3lips /opt/3lips
sudo docker compose up -d —build
```

The API front-end is available at [http://localhost:49156](http://localhost:49156).

## Method of Operation

The association uses the following algorithm:

- ADS-B associator will associate the highest SNR target within some delay and Doppler boundary around the truth.

The target localisation uses 1 of the following algorithms:

- **Ellipse parametric** samples an ellipse (2D) at 0 altitude. Find intersections between 3 or more ellipses such that the distance to each point is under some threshold.

- **Ellipsoid parametric** samples an ellipsoid (3D). Find intersections between 3 or more ellipsoids such that the distance to each point is under some threshold.

- **Spherical intersection** a closed form solution which applies when a common receiver or transmitter are used. As described in [Two Methods for Target Localization in Multistatic Passive Radar](https://ieeexplore.ieee.org/document/6129656).

The system architecture is as follows:

- The API server and HTML pages are served through a [Flask](http://github.com/pallets/flask) in Python.
- An initial API request with a new set of parameters (algorithms or radar nodes) will add these parameters to a common processing loop. This is so fair comparisons can be made between these parameters on the same input data.
- A set of API parameters will continue to be processed unless there is no API call in some specified time - see *main.py* to update. This allows the latest geolocation to be provided, rather than adding to the processing loop and waiting for the update from the next time increment.

## Future Work

- Implement an association algorithm that is not reliant on ADS-B truth.
- Choose to use detection or track data from each radar.
- Long term plots to show metrics such as 2D location accuracy to ADS-B, number of aircraft tracked, etc.
- Scale number of samples in ellipse/ellipsoid to size of shape.

## License

[MIT](http://choosealicense.com/licenses/mit)