.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/plot_micro_doppler.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_auto_examples_plot_micro_doppler.py>`
        to download the full example code.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_plot_micro_doppler.py:


Micro-Doppler time-frequency analysis
=====================================

Resolve a sinusoidally varying radial velocity with a radar-aware STFT.  The
same result carries frequency, time, and velocity coordinates.

.. GENERATED FROM PYTHON SOURCE LINES 8-50



.. image-sg:: /auto_examples/images/sphx_glr_plot_micro_doppler_001.png
   :alt: Micro-Doppler spectrogram
   :srcset: /auto_examples/images/sphx_glr_plot_micro_doppler_001.png
   :class: sphx-glr-single-img





.. code-block:: Python


    from __future__ import annotations

    import numpy as np
    from matplotlib import pyplot as plt

    from pyradar.base import Radar
    from pyradar.rsp import micro_doppler_spectrogram

    radar = Radar.awr1843_rampcnn()
    sampleRate = 1.0 / radar.slowTimeInterval
    time = np.arange(512) / sampleRate
    meanVelocity = 0.5
    microVelocity = 1.2
    motionFrequency = 25.0

    # Doppler phase is the time integral of 2 v(t) / wavelength.
    phaseCycles = (2.0 / radar.wavelength) * (
        meanVelocity * time
        + microVelocity
        * np.sin(2.0 * np.pi * motionFrequency * time)
        / (2.0 * np.pi * motionFrequency)
    )
    slowTimeSignal = np.exp(2j * np.pi * phaseCycles)
    result = micro_doppler_spectrogram(
        slowTimeSignal,
        radar=radar,
        segmentLength=96,
        overlap=88,
        fftSize=256,
    )

    figure, axis = plt.subplots(figsize=(7, 3.8), constrained_layout=True)
    powerDb = 10.0 * np.log10(np.maximum(result.power, np.finfo(float).tiny))
    image = axis.pcolormesh(result.time, result.velocity, powerDb, shading="auto")
    axis.set(
        xlabel="Time (s)",
        ylabel="Radial velocity (m/s)",
        title="Micro-Doppler spectrogram",
    )
    figure.colorbar(image, ax=axis, label="Power (dB)")
    plt.show()


.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 0.191 seconds)


.. _sphx_glr_download_auto_examples_plot_micro_doppler.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: plot_micro_doppler.ipynb <plot_micro_doppler.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: plot_micro_doppler.py <plot_micro_doppler.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: plot_micro_doppler.zip <plot_micro_doppler.zip>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_