Scripts for processing Millstone Hill radar data to detect and analyze meteor head echoes.

First, get a copy of this repository by either downloading it or using git clone:

git clone https://github.com/ryanvolz/millstone_meteor

For installating dependencies and managing environments, I recommend micromamba. micromamba is a self-contained executable that can be used in place of conda to create environments and install packages. You can simply download the latest version for your platform and run directly it with the typical conda commands: ./micromamba activate ENV. But the gentlest approach is to follow the installation instructions provided by prefix.dev.

Once you have micromamba/mamba/conda, create and activate an environment for running the millstone_meteor code:

micromamba create -n meteor
micromamba activate meteor
micromamba config prepend channels conda-forge
micromamba config set channel_priority strict

Then from within the environment you just created, install the following dependencies:

micromamba install dask digital_rf h5netcdf ipython matplotlib numba numpy pandas scipy xarray zarr

The millstone_meteor code should now be able to run from within the activated conda environment.

The processing is run by either by importing the detect_meteors module and running the detect_meteors(...) function, or by running detect_meteors.py as a terminal script. Command line arguments for the script can be viewed by running:

python detect_meteors.py --help

An example command is as follows:

python detect_meteors.py --snr_thresh=20 --pointing_el 13.3 --amin 70 --amax 120 --vmin=-72 --vmax 72 --eps 20 --min_samples 8 --tscale 0.0041 --rscale 150 --vscale 262.1 -c misa-l -t misa-l --offsets "10000001=15" -i /data/2022-08-12_meteor/id_metadata -o /data/2022-08-12_meteor/output --tmm /data/tmm.hdf5 /data/2022-08-12_meteor