.. note:: :class: sphx-glr-download-link-note Click :ref:`here ` to download the full example code .. rst-class:: sphx-glr-example-title .. _sphx_glr_auto_examples_plot_4_1_3_chirps_ambifunb.py: ============================================================== Narrow Band Ambiguity Function of Chirps with Different Slopes ============================================================== This example demonstrates the narrow band ambiguity function (AF) of a signal composed of two chirps with Gaussian amplitude modulation but havind linear frequency modulations with different slopes. Note that the AF interference terms are located away from the origin. Figure 4.13 from the tutorial. .. image:: /auto_examples/images/sphx_glr_plot_4_1_3_chirps_ambifunb_001.png :class: sphx-glr-single-img .. code-block:: default from tftb.generators import fmlin, amgauss from tftb.processing.ambiguity import narrow_band import numpy as np import matplotlib.pyplot as plt n_points = 64 sig1 = fmlin(n_points, 0.2, 0.5)[0] * amgauss(n_points) sig2 = fmlin(n_points, 0.3, 0)[0] * amgauss(n_points) sig = np.hstack((sig1, sig2)) tfr, x, y = narrow_band(sig) plt.contour(2 * x, y, np.abs(tfr) ** 2, 16) plt.title('Narrow Band ambiguity function') plt.xlabel('Delay') plt.ylabel('Doppler') plt.grid(True) plt.show() .. rst-class:: sphx-glr-timing **Total running time of the script:** ( 0 minutes 0.156 seconds) .. _sphx_glr_download_auto_examples_plot_4_1_3_chirps_ambifunb.py: .. only :: html .. container:: sphx-glr-footer :class: sphx-glr-footer-example .. container:: sphx-glr-download :download:`Download Python source code: plot_4_1_3_chirps_ambifunb.py ` .. container:: sphx-glr-download :download:`Download Jupyter notebook: plot_4_1_3_chirps_ambifunb.ipynb ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_