Welcome to the course material for the MIT Lincoln Laboratory Introduction to Radar class. The main lectures come in the form of Jupyter notebooks with interactive elements. The easiest way to try out the course is to use the notebooks hosted by Binder: simply click the launch button below.
If you would like to keep a working copy of all notebooks and experience the smoothest animations, a local installation is probably the best choice. This can be done quickly by installing Python, creating a virtual environment, and installing the necessary dependencies. Below you will find step-by-step directions for different operating systems.
You can download the course as a ZIP file here. After downloading the ZIP archive, extract it to a desired path (referred to later as <radar-course-path>).
If you have not, first install Python on your system; you can download the Python installer from here.
Next, we will have to make a virtual environment to run JupyterLab and the radar course. A virtual environment is a minimal, isolated copy of Python that will keep the lab software from interfering with your other Python projects; you can read more about them here.
To create our virtual environment, first create a folder of your choice, which will now be referred to as <venv-dir>. After creating the directory, open a command prompt and run:
cd <venv-dir>
py -m venv .
This will construct the Python virtual environment in this directory. Next, we will activate the virtual environment. Staying in the <venv-dir> directory, run:
.\Scripts\activate
The command prompt should now show that you are in your virtual environment, i.e., if the virtual environment directory was c:\test, the command prompt should now look like
(test) c:\test>
Next, we will install the necessary prerequisite packages. To do this, we move to radar course directory and use the Python installation routine pip by typing:
cd <radar-course-path>
pip install -r requirements.txt
Note: If you are behind a proxy server at <proxy-address>, you will have to run pip using:
pip install --proxy <proxy-address> -r requirements.txt
To start the labs, we first start with a new terminal/command prompt and activating the virtual environment by typing:
cd <venv-dir>
.\Scripts\activate
Navigate to the path of the radar course material:
cd <radar-course-path>
Lastly, we can start JupyterLab in the current location:
jupyter lab
You can download the course as a ZIP file here. After downloading the ZIP archive, extract it to a desired path (referred to later as <radar-course-path>).
If you have not, first install Python on your system; you can download the Python installer from here.
Next, we will have to make a virtual environment to run JupyterLab and the radar course. A virtual environment is a minimal, isolated copy of Python that will keep the lab software from interfering with your other Python projects; you can read more about them here.
To create our virtual environment, first create a folder of your choice, which will now be referred to as <venv-dir>. After creating the directory, open a command prompt and run:
cd <venv-dir>
python3 -m venv .
This will construct the Python virtual environment in this directory. Next, we will activate the virtual environment. Staying in the <venv-dir> directory, run:
source ./bin/activate
The terminal should now show that you are in your virtual environment, i.e., if the virtual environment directory was ~/test, the command prompt should now look like
(test) user@machine:~/test$
Next, we will install the necessary prerequisite packages. To do this, we move to radar course directory and use the Python installation routine pip by typing:
cd <radar-course-path>
pip install -r requirements.txt
Note: If you are behind a proxy server at <proxy-address>, you will have to run pip using:
pip install --proxy <proxy-address> -r requirements.txt
To start the labs, we first start with a new terminal/command prompt and type:
cd <venv-dir>
source ./bin/activate
Navigate to the path of the radar course material:
cd <radar-course-path>
Lastly, we can start JupyterLab in the current location:
jupyter lab
You can download the course as a ZIP file here. After downloading the ZIP archive, extract it to a desired path (referred to later as <radar-course-path>).
If you have not, first install Python on your system. This can be done using apt by:
sudo apt update
sudo apt install python3 python3-venv
Next, we will have to make a virtual environment to run JupyterLab and the radar course. A virtual environment is a minimal, isolated copy of Python that will keep the lab software from interfering with your other Python projects; you can read more about them here.
To create our virtual environment, first create a folder of your choice, which will now be referred to as <venv-dir>. After creating the directory, open a command prompt and run:
cd <venv-dir>
python3 -m venv .
This will construct the Python virtual environment in this directory. Next, we will activate the virtual environment. Staying in the <venv-dir> directory, run:
source ./bin/activate
The terminal should now show that you are in your virtual environment, i.e., if the virtual environment directory was ~/test, the command prompt should now look like
(test) user@machine:~/test$
Next, we will install the necessary prerequisite packages. To do this, we move to radar course directory and use the Python installation routine pip by typing:
cd <radar-course-path>
pip install -r requirements.txt
Note: If you are behind a proxy server at <proxy-address>, you will have to run pip using:
pip install --proxy <proxy-address> -r requirements.txt
To start the labs, we first start with a new terminal/command prompt and type:
cd <venv-dir>
source ./bin/activate
Navigate to the path of the radar course material:
cd <radar-course-path>
Lastly, we can start JupyterLab in the current location:
jupyter lab
Zachary Chance, Robert Freking, Victoria Helus
MIT Lincoln Laboratory Lexington, MA 02421
DISTRIBUTION STATEMENT A. Approved for public release. Distribution is unlimited.
This material is based upon work supported by the United States Air Force under Air Force Contract No. FA8702-15-D-0001. Any opinions, findings, conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the United States Air Force.
© 2022 Massachusetts Institute of Technology.
The software/firmware is provided to you on an As-Is basis
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RAMS ID: 1016938