{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "93c40dea",
   "metadata": {},
   "source": [
    "# FMCW Intro - Target speed\n",
    "\n",
    "You can open this workbook in Google Colab to experiment with mmWrt \n",
    "[![](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/matt-chv/mmWrt/blob/main/docs/Speed.ipynb)\n",
    "\n",
    "Below is an intro to mmWrt for simple targets position and speed estimation based on 2D FFT Range Doppler\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "df9597cc",
   "metadata": {},
   "source": [
    "## The problem\n",
    "\n",
    "As distance changes over time, how can FMCW radar measure speed ?\n",
    "\n",
    "## The solution\n",
    "\n",
    "A 2D FFT will allow to measure the speed of the targets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a484170f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "running from git folder, using local path (latest) mmWrt code c:\\git\\mmWrt\n",
      "2024-05-23 14:24:57.278064\n"
     ]
    }
   ],
   "source": [
    "# Install a pip package in the current Jupyter kernel\n",
    "import sys\n",
    "from os.path import abspath, basename, join, pardir\n",
    "import datetime\n",
    "\n",
    "# hack to handle if running from git cloned folder or stand alone (like Google Colab)\n",
    "cw = basename(abspath(join(\".\")))\n",
    "dp = abspath(join(\".\",pardir))\n",
    "if cw==\"docs\" and basename(dp) == \"mmWrt\":\n",
    "    # running from cloned folder\n",
    "    print(\"running from git folder, using local path (latest) mmWrt code\", dp)\n",
    "    sys.path.insert(0, dp)\n",
    "else:\n",
    "    print(\"running standalone, need to ensure mmWrt is installed\")\n",
    "    !{sys.executable} -m pip install mmWrt\n",
    "print(datetime.datetime.now())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "242be93b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0.6-pre.1\n"
     ]
    }
   ],
   "source": [
    "from os.path import abspath, join, pardir\n",
    "import sys\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.cm as cm\n",
    "from matplotlib import colors\n",
    "from numpy import where, expand_dims\n",
    "from numpy import complex_ as complex\n",
    "\n",
    "# uncomment below if the notebook is launched from project's root folder\n",
    "# dp = abspath(join(\".\",pardir))\n",
    "# sys.path.insert(0, dp)\n",
    "\n",
    "\n",
    "from mmWrt.Raytracing import rt_points  # noqa: E402\n",
    "from mmWrt.Scene import Radar, Transmitter, Receiver, Target  # noqa: E402\n",
    "from mmWrt import RadarSignalProcessing as rsp  # noqa: E402\n",
    "from mmWrt import __version__ as mmWrt_ver\n",
    "print(mmWrt_ver)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c8d1d8c",
   "metadata": {},
   "source": [
    "## Step by step\n",
    "\n",
    "Looking at multiple 1D FFT before doing a 2D FFT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "d8d8e108",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "32\n",
      "(32, 64)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x282ae86e010>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from scipy.fft import fft, fft2\n",
    "c = 3e8\n",
    "\n",
    "debug_ON = False\n",
    "test = 0\n",
    "NC=32\n",
    "NA=64\n",
    "fs0 = 1e5\n",
    "slope0 = 28e10\n",
    "tic0 = 1.2e-3\n",
    "radar = Radar(transmitter=Transmitter(bw=0.2e9, slope=slope0,\n",
    "                                      t_inter_chirp=tic0,\n",
    "                                      chirps_count=NC),\n",
    "              receiver=Receiver(fs=fs0, n_adc=NA, max_adc_buffer_size=256,\n",
    "                                debug=debug_ON), debug=debug_ON)\n",
    "\n",
    "x1, v1 = 5, 0\n",
    "target1 = Target(xt=lambda t: v1*t+x1)\n",
    "x2, v2 = 3, 0.6\n",
    "target2 = Target(xt=lambda t: v2*t+x2)\n",
    "\n",
    "targets = [target1, target2]\n",
    "\n",
    "bb = rt_points(radar, targets, datatype=complex, debug=debug_ON)\n",
    "print(bb[\"chirps_count\"])\n",
    "cube = bb[\"adc_cube\"][0,:,0,0,:]\n",
    "print(cube.shape)\n",
    "Z_fft2 = abs(fft2(cube))\n",
    "Data_fft2 = Z_fft2\n",
    "\n",
    "plt.xlabel(\"Range\")\n",
    "plt.ylabel(\"Velocity\")\n",
    "plt.title('Velocity-Range 2D FFT')\n",
    "plt.imshow(Data_fft2[0:NC//2,:NA//2])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "61c36205-f026-4967-852b-8f22e234caf9",
   "metadata": {},
   "source": [
    "## Plotting the Range Doppler with units\n",
    "\n",
    "> leveraging the plot_range_doppler utility function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "ed4a514b-7374-4656-a207-8ad7de4356ff",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.patches.Circle at 0x282ae8e5c10>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from mmWrt.Plots import plot_range_doppler\n",
    "fig, _, _ = plot_range_doppler(bb[\"adc_cube\"][0,:,0,0,:], radar, no_speed_shift=False)\n",
    "\n",
    "# adding comments in picture\n",
    "fig.text(0.3, 0.5, f\"target1: @d={x1}, v={v1}\", color=\"white\", fontsize=12)\n",
    "target1 = plt.Circle((0.22, 0.48), 0.05, fill=False, color=\"white\")\n",
    "fig.text(0.30, 0.25, f\"target2: @d={x2}, v={v2}\", color=\"white\", fontsize=12)\n",
    "target2 = plt.Circle((0.2, 0.25), 0.05, fill=False, color=\"white\")\n",
    "fig.add_artist(target1)\n",
    "fig.add_artist(target2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "88123e00-3d39-49de-a7cb-0885d88105fa",
   "metadata": {},
   "source": [
    "## Illustration of 1D FFT and 2D FFT"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e630151e-2526-42b5-ae42-8f92907b606a",
   "metadata": {},
   "source": [
    "### Plot all the range FFT\n",
    "\n",
    "> Scroll output of next cell to see all the range FFTs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "b92cc7a7",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\matth\\AppData\\Local\\Temp\\ipykernel_8940\\2651558762.py:2: MatplotlibDeprecationWarning: The get_cmap function was deprecated in Matplotlib 3.7 and will be removed two minor releases later. Use ``matplotlib.colormaps[name]`` or ``matplotlib.colormaps.get_cmap(obj)`` instead.\n",
      "  cmap = cm.get_cmap(name='CMRmap_r')\n"
     ]
    },
    {
     "data": {
      "image/png": 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iGi+NjY2qqKhQQUHBtyd0u1VQUKDy8vIWjykvLw9aL0ljxow56/qSkhIlJSUFtqysrO/vJwAAAGJOROOlpqZGzc3NSk9PD9qfnp4un8/X4jE+n++c1s+fP1+1tbWBrbKy8vsZHgAAxKT4aA8QLo/HI4/HE+0xAADAeRLRV15SU1MVFxenqqqqoP1VVVXyer0tHuP1es9pPQAAuLhENF4SEhKUm5urjRs3Bvb5/X5t3LhR+fn5LR6Tn58ftF6SNmzYcNb1AADg4hLxt43mzp2rKVOmaNiwYRo+fLiWLVum+vp6TZs2TZJ0xx13qHv37iopKZEk3XPPPbr22mv1+OOP6/rrr9eaNWu0bds2Pfvss5EeFQAAGBDxeJkwYYK++OILLViwQD6fT0OHDlVpaWngQ7kHDx6U2/3tC0BXXXWVVq9erd/97nd66KGHdNlll+nVV1/VoEGDIj0qAAAw4Lx8YLeoqEhFRUUtPlZWVnbGvltuuUW33HJLhKcCAAAW8W8bAQAAU4gXAABgCvECAABMIV4AAIApxAsAADCFeAEAAKYQLwAAwBTiBQAAmEK8AAAAU4gXAABgCvECAABMIV4AAIApxAsAADCFeAEAAKYQLwAAwBTiBQAAmEK8AAAAU4gXAABgCvECAABMIV4AAIApxAsAADCFeAEAAKYQLwAAwBTiBQAAmEK8AAAAU4gXAABgCvECAABMIV4AAIApxAsAADCFeAEAAKYQLwAAwBTiBQAAmEK8AAAAU4gXAABgCvECAABMIV4AAIApxAsAADCFeAEAAKYQLwAAwBTiBQAAmEK8AAAAU4gXAABgCvECAABMIV4AAIApxAsAADCFeAEAAKYQLwAAwBTiBQAAmEK8AAAAU4gXAABgCvECAABMIV4AAIApxAsAADCFeAEAAKYQLwAAwBTiBQAAmEK8AAAAU4gXAABgCvECAABMIV4AAIApxAsAADCFeAEAAKYQLwAAwJTzEi/Lly9Xdna2EhMTlZeXp61bt5517XPPPacRI0aoa9eu6tq1qwoKClpdDwAALi4Rj5e1a9dq7ty5Ki4u1vbt25WTk6MxY8aourq6xfVlZWWaNGmS3n77bZWXlysrK0ujR4/W559/HulRAQCAARGPl6VLl2rGjBmaNm2aBg4cqBUrVqhjx4568cUXW1y/atUq3XXXXRo6dKgGDBig559/Xn6/Xxs3bmxx/alTp1RXVxe0AQCAC1dE46WxsVEVFRUqKCj49oRutwoKClReXt6u52hoaFBTU5NSUlJafLykpERJSUmBLSsr63uZHQAAxKaIxktNTY2am5uVnp4etD89PV0+n69dz/Hggw8qMzMzKID+1/z581VbWxvYKisrw54bAADErvhoD9CaxYsXa82aNSorK1NiYmKLazwejzwez3meDAAAREtE4yU1NVVxcXGqqqoK2l9VVSWv19vqsUuWLNHixYv11ltvaciQIZEcEwAAGBLRt40SEhKUm5sb9GHbbz58m5+ff9bjHnvsMS1atEilpaUaNmxYJEcEAADGRPxto7lz52rKlCkaNmyYhg8frmXLlqm+vl7Tpk2TJN1xxx3q3r27SkpKJEmPPvqoFixYoNWrVys7Ozvw2ZhOnTqpU6dOkR4XAADEuIjHy4QJE/TFF19owYIF8vl8Gjp0qEpLSwMf4j148KDc7m9fAHrmmWfU2NioX/7yl0HPU1xcrIULF0Z6XAAAEOPOywd2i4qKVFRU1OJjZWVlQV8fOHAg8gMBAACz+LeNAACAKcQLAAAwhXgBAACmEC8AAMAU4gUAAJhCvAAAAFOIFwAAYArxAgAATCFeAACAKcQLAAAwhXgBAACmEC8AAMAU4gUAAJhCvAAAAFOIFwAAYArxAgAATCFeAACAKcQLAAAwhXgBAACmEC8AAMAU4gUAAJhCvAAAAFOIFwAAYArxAgAATCFeAACAKcQLAAAwhXgBAACmEC8AAMAU4gUAAJhCvAAAAFOIFwAAYArxAgAATCFeAACAKcQLAAAwhXgBAACmEC8AAMAU4gUAAJhCvAAAAFOIFwAAYArxAgAATCFeAACAKcQLAAAwhXgBAACmEC8AAMAU4gUAAJhCvAAAAFOIFwAAYArxAgAATCFeAACAKcQLAAAwhXgBAACmEC8AAMAU4gUAAJhCvAAAAFOIFwAAYArxAgAATCFeAACAKcQLAAAwhXgBAACmEC8AAMAU4gUAAJhCvAAAAFPOS7wsX75c2dnZSkxMVF5enrZu3dqu49asWSOXy6Xx48dHdkAAAGBGxONl7dq1mjt3roqLi7V9+3bl5ORozJgxqq6ubvW4AwcO6P7779eIESMiPSIAADAk4vGydOlSzZgxQ9OmTdPAgQO1YsUKdezYUS+++OJZj2lubtbkyZP18MMPq0+fPpEeEQAAGBLReGlsbFRFRYUKCgq+PaHbrYKCApWXl5/1uEceeUTdunXT9OnT2zzHqVOnVFdXF7QBAIALV0TjpaamRs3NzUpPTw/an56eLp/P1+Ix7777rl544QU999xz7TpHSUmJkpKSAltWVlbYcwMAgNgVU99tdPz4cd1+++167rnnlJqa2q5j5s+fr9ra2sBWWVkZ4SkBAEA0xUfyyVNTUxUXF6eqqqqg/VVVVfJ6vWes37dvnw4cOKAbbrghsM/v9389aHy89uzZo759+wYd4/F45PF4IjA9AACIRRF95SUhIUG5ubnauHFjYJ/f79fGjRuVn59/xvoBAwboo48+0s6dOwPbL37xC/30pz/Vzp07eUsIAABE9pUXSZo7d66mTJmiYcOGafjw4Vq2bJnq6+s1bdo0SdIdd9yh7t27q6SkRImJiRo0aFDQ8cnJyZJ0xn4AAHBxini8TJgwQV988YUWLFggn8+noUOHqrS0NPAh3oMHD8rtjqmP3gAAgBgW8XiRpKKiIhUVFbX4WFlZWavHrly58vsfCAAAmMVLHgAAwBTiBQAAmEK8AAAAU4gXAABgCvECAABMIV4AAIApxAsAADCFeAEAAKYQLwAAwBTiBQAAmEK8AAAAU4gXAABgCvECAABMIV4AAIApxAsAADCFeAEAAKYQLwAAwBTiBQAAmEK8AAAAU4gXAABgCvECAABMIV4AAIApxAsAADCFeAEAAKYQLwAAwBTiBQAAmEK8AAAAU4gXAABgCvECAABMiY/2AN83x3EkSV81nwr5Ob7yu0I+trG5IeRjJam5+WTIx/r9TWGdO5xrFq66Jn/Ixx4/5YR1bv9XYRzfEN65lRj6z1vO6fDOfTqM+6WxMbxzN4Z+r7k7hP5rRJLi478K63i3OyGMY0P/vUWS4uJCP94d5v+qut2h328uV3i/N7ndoR/vcoV3r7pcof8xGc6x0T53NNTV1Un69s/x1ric9qwy5NChQ8rKyor2GAAAIASVlZXq0aNHq2suuHjx+/06fPiwOnfuLJfrzP9LqaurU1ZWliorK9WlS5coTGgP1yw0XLdzxzULDdft3HHNQhPJ6+Y4jo4fP67MzEy523ip0N7rSm1wu91tFpskdenShRv2HHHNQsN1O3dcs9Bw3c4d1yw0kbpuSUlJ7VrHB3YBAIApxAsAADDloosXj8ej4uJieTyeaI9iBtcsNFy3c8c1Cw3X7dxxzUITK9ftgvvALgAAuLBddK+8AAAA24gXAABgCvECAABMIV4AAIApxAsAADDlooqX5cuXKzs7W4mJicrLy9PWrVujPVJMW7hwoVwuV9A2YMCAaI8Vc9555x3dcMMNyszMlMvl0quvvhr0uOM4WrBggTIyMnTJJZeooKBAn376aXSGjRFtXbOpU6eece8VFhZGZ9gYUVJSoiuvvFKdO3dWt27dNH78eO3ZsydozcmTJzV79mz94Ac/UKdOnXTzzTerqqoqShPHhvZct5EjR55xv915551Rmjj6nnnmGQ0ZMiTwt+jm5+frX//6V+DxWLjPLpp4Wbt2rebOnavi4mJt375dOTk5GjNmjKqrq6M9Wkz70Y9+pCNHjgS2d999N9ojxZz6+nrl5ORo+fLlLT7+2GOP6cknn9SKFSu0ZcsWXXrppRozZoxOngzvX0e2rK1rJkmFhYVB997LL798HieMPZs3b9bs2bP1/vvva8OGDWpqatLo0aNVX18fWHPvvffqjTfe0CuvvKLNmzfr8OHDuummm6I4dfS157pJ0owZM4Lut8ceeyxKE0dfjx49tHjxYlVUVGjbtm362c9+pnHjxunjjz+WFCP3mXORGD58uDN79uzA183NzU5mZqZTUlISxaliW3FxsZOTkxPtMUyR5Kxfvz7wtd/vd7xer/PHP/4xsO/YsWOOx+NxXn755ShMGHu+e80cx3GmTJnijBs3LirzWFFdXe1IcjZv3uw4ztf3VYcOHZxXXnklsGb37t2OJKe8vDxaY8ac7143x3Gca6+91rnnnnuiN5QBXbt2dZ5//vmYuc8uildeGhsbVVFRoYKCgsA+t9utgoIClZeXR3Gy2Pfpp58qMzNTffr00eTJk3Xw4MFoj2TK/v375fP5gu69pKQk5eXlce+1oaysTN26dVP//v01a9Ysffnll9EeKabU1tZKklJSUiRJFRUVampqCrrXBgwYoJ49e3Kv/Y/vXrdvrFq1SqmpqRo0aJDmz5+vhoaGaIwXc5qbm7VmzRrV19crPz8/Zu6zC+5flW5JTU2NmpublZ6eHrQ/PT1dn3zySZSmin15eXlauXKl+vfvryNHjujhhx/WiBEjtGvXLnXu3Dna45ng8/kkqcV775vHcKbCwkLddNNN6t27t/bt26eHHnpI1113ncrLyxUXFxft8aLO7/frt7/9rX7yk59o0KBBkr6+1xISEpScnBy0lnvtWy1dN0m69dZb1atXL2VmZurDDz/Ugw8+qD179mjdunVRnDa6PvroI+Xn5+vkyZPq1KmT1q9fr4EDB2rnzp0xcZ9dFPGC0Fx33XWBHw8ZMkR5eXnq1auX/va3v2n69OlRnAwXuokTJwZ+PHjwYA0ZMkR9+/ZVWVmZRo0aFcXJYsPs2bO1a9cuPoN2js523WbOnBn48eDBg5WRkaFRo0Zp37596tu37/keMyb0799fO3fuVG1trf7+979rypQp2rx5c7THCrgo3jZKTU1VXFzcGZ+GrqqqktfrjdJU9iQnJ+uHP/yh9u7dG+1RzPjm/uLeC0+fPn2UmprKvSepqKhIb775pt5++2316NEjsN/r9aqxsVHHjh0LWs+99rWzXbeW5OXlSdJFfb8lJCSoX79+ys3NVUlJiXJycvTEE0/EzH12UcRLQkKCcnNztXHjxsA+v9+vjRs3Kj8/P4qT2XLixAnt27dPGRkZ0R7FjN69e8vr9Qbde3V1ddqyZQv33jk4dOiQvvzyy4v63nMcR0VFRVq/fr02bdqk3r17Bz2em5urDh06BN1re/bs0cGDBy/qe62t69aSnTt3StJFfb99l9/v16lTp2LnPjtvHw2OsjVr1jgej8dZuXKl89///teZOXOmk5yc7Ph8vmiPFrPuu+8+p6yszNm/f7/z3nvvOQUFBU5qaqpTXV0d7dFiyvHjx50dO3Y4O3bscCQ5S5cudXbs2OF89tlnjuM4zuLFi53k5GTntddecz788ENn3LhxTu/evZ2vvvoqypNHT2vX7Pjx487999/vlJeXO/v373feeust54orrnAuu+wy5+TJk9EePWpmzZrlJCUlOWVlZc6RI0cCW0NDQ2DNnXfe6fTs2dPZtGmTs23bNic/P9/Jz8+P4tTR19Z127t3r/PII48427Ztc/bv3++89tprTp8+fZxrrrkmypNHz7x585zNmzc7+/fvdz788ENn3rx5jsvlcv797387jhMb99lFEy+O4zhPPfWU07NnTychIcEZPny48/7770d7pJg2YcIEJyMjw0lISHC6d+/uTJgwwdm7d2+0x4o5b7/9tiPpjG3KlCmO43z97dK///3vnfT0dMfj8TijRo1y9uzZE92ho6y1a9bQ0OCMHj3aSUtLczp06OD06tXLmTFjxkX/PxotXS9Jzl/+8pfAmq+++sq56667nK5duzodO3Z0brzxRufIkSPRGzoGtHXdDh486FxzzTVOSkqK4/F4nH79+jkPPPCAU1tbG93Bo+jXv/6106tXLychIcFJS0tzRo0aFQgXx4mN+8zlOI5z/l7nAQAACM9F8ZkXAABw4SBeAACAKcQLAAAwhXgBAACmEC8AAMAU4gUAAJhCvAAAAFOIFwAAYArxAgAATCFeAACAKcQLAAAw5f8DYlI5+xd+FGsAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bb = rt_points(radar, targets, debug=debug_ON)\n",
    "cmap = cm.get_cmap(name='CMRmap_r')\n",
    "ffts = []\n",
    "for chirp_i in range(15):\n",
    "    adc = bb[\"adc_cube\"][0,chirp_i,0,0,:]\n",
    "    range_profile = fft(adc)\n",
    "\n",
    "    mag_r = abs(range_profile[:len(range_profile)//2])\n",
    "    mag_r = expand_dims(mag_r, axis=0)\n",
    "    plt.imshow(mag_r, cmap,\n",
    "           aspect='auto',\n",
    "           norm=colors.LogNorm(vmin=min(mag_r[0][:]), vmax=max(mag_r[0][:])))\n",
    "    plt.title(\"1D FFT\")\n",
    "    # plt.savefig(fp_fft_1D)\n",
    "    plt.show()\n",
    "    ffts.append(range_profile[:21])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b3c3b723-bfbb-4c85-8913-d8a52276b656",
   "metadata": {},
   "source": [
    "### Range FFT on cube\n",
    "\n",
    "> 1D FFT on 2D cube, shows 2 targets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "aacf8578",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x282ae9709d0>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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iS05Ojt8tAQCAGOV7ELnnnnt077336uqrr9bQoUM1ceJE3XXXXSoqKmpx/IwZM1RVVRVZysrK/G4JAADEKN//NLNv3z4FAs3zTUJCgsLhcIvjg8GggsGg320AAIA44HsQGTt2rB5++GHl5uZq8ODB2rJli5566ildf/31fm8KAADEOd+DyDPPPKOZM2fqtttuU0VFhbKzs3XzzTfrvvvu83tTAAAgzvkeRNLS0jR79mzNnj3b79IAAKCL4VozAADAGYIIAABwhiACAACcIYgAAABnCCIAAMAZ378145dAIEWBQIqV2uGwnbqSJC/BXm1JJmCs1Q6o5R+d801CqtXyZXWrrNVuarrIWu1/ybJaPcHiP8tWfqvQN7ZeByTJ86yVliQZe4frv+sfsFbb82L27cE528+NzXm1qbN9c0YEAAA4QxABAADOEEQAAIAzBBEAAOAMQQQAADhDEAEAAM4QRAAAgDMEEQAA4AxBBAAAOEMQAQAAzhBEAACAMwQRAADgDEEEAAA4QxABAADOEEQAAIAzBBEAAOAMQQQAADhDEAEAAM4QRAAAgDMEEQAA4AxBBAAAOEMQAQAAzhBEAACAM4muG2jN/qoPlBgO2ineVGOnriR9t81ebUnJX/W2VvvE5C+t1ZYknTDcavmvvvqdtdoJCeOs1f5X/R5W6ycm2qvveSnWav+rvr2XKZu1j0b9GH4Jb5f95wYtsfm8JyR07twGZ0QAAIAzBBEAAOAMQQQAADhDEAEAAM4QRAAAgDMEEQAA4AxBBAAAOBN1EFm7dq3Gjh2r7OxseZ6npUuXNnvcGKP77rtPffv2VWpqqvLz87Vjxw6/+gUAAF1I1EGkrq5Ow4YN05w5c1p8/PHHH9fTTz+tefPmacOGDerWrZtGjx6t+vr6I24WAAB0LVH/xFpBQYEKCgpafMwYo9mzZ+s3v/mNxo371y9Rvvjii8rMzNTSpUt19dVXH1m3AACgS/H1MyKlpaUqLy9Xfn5+5L6MjAwNHz5c69ata3GdhoYGVVdXN1sAAMCxwdcgUl5eLknKzMxsdn9mZmbksUMVFRUpIyMjsuTk5PjZEgAAiGHOvzUzY8YMVVVVRZaysjLXLQEAgKPE1yCSlZUlSdq7d2+z+/fu3Rt57FDBYFDp6enNFgAAcGzwNYjk5eUpKytLK1eujNxXXV2tDRs2aMSIEX5uCgAAdAFRf2umtrZWO3fujNwuLS3V1q1b1bNnT+Xm5mrq1Kn67W9/q5NPPll5eXmaOXOmsrOzNX78eD/7BgAAXUDUQWTTpk0aNWpU5Pa0adMkSZMmTdLChQv161//WnV1dbrppptUWVmpH/zgB1q2bJlSUlL86xoAAHQJUQeRkSNHyhjT6uOe5+nBBx/Ugw8+eESNAQCArs/5t2YAAMCxiyACAACcIYgAAABnCCIAAMCZqD+serT06nuH0tPTrNRuamr55+b9UNXtHWu1Jalu4P+2VnvrB4Os1ZakK7560Wr9U06ZZa12KFRprbYkeZ7dQzEcrrVWOxCw+404z7NX3/bzHt/147n3+Bavz82BAzWdWo8zIgAAwBmCCAAAcIYgAgAAnCGIAAAAZwgiAADAGYIIAABwhiACAACcIYgAAABnCCIAAMAZgggAAHCGIAIAAJwhiAAAAGcIIgAAwBmCCAAAcIYgAgAAnCGIAAAAZwgiAADAGYIIAABwhiACAACcIYgAAABnCCIAAMAZgggAAHCGIAIAAJxJdN1Aa74tn6PGuqCd4gf22akrSf+z1V5tSek7+1ir/f3k3dZqS5IyBlotnyZ7z0337iOt1ZakQCAljuvbfRnxPHv1bdY+GuK9f1t4XtxITq7u1HqcEQEAAM4QRAAAgDMEEQAA4AxBBAAAOEMQAQAAzhBEAACAMwQRAADgTNRBZO3atRo7dqyys7PleZ6WLl0aeaypqUnTp0/X0KFD1a1bN2VnZ+vaa6/Vnj17/OwZAAB0EVEHkbq6Og0bNkxz5sw57LF9+/apuLhYM2fOVHFxsd58802VlJTosssu86VZAADQtUT983MFBQUqKCho8bGMjAytWLGi2X3PPvuszjvvPO3evVu5ubmd6xIAAHRJ1n8Ht6qqSp7nqUePHi0+3tDQoIaGhsjt6urO/UQsAACIP1Y/rFpfX6/p06frmmuuUXp6eotjioqKlJGREVlycnJstgQAAGKItSDS1NSkK6+8UsYYzZ07t9VxM2bMUFVVVWQpKyuz1RIAAIgxVv40czCE7Nq1S++//36rZ0MkKRgMKhi0dJVdAAAQ03wPIgdDyI4dO7Rq1Sr16tXL700AAIAuIuogUltbq507d0Zul5aWauvWrerZs6f69u2rn//85youLtY777yjUCik8vJySVLPnj2VnJzsX+cAACDuRR1ENm3apFGjRkVuT5s2TZI0adIk3X///Xr77bclSWeccUaz9VatWqWRI0d2vlMAANDlRB1ERo4cKWNMq4+39RgAAMB/41ozAADAGYIIAABwhiACAACcIYgAAABnCCIAAMAZ6xe966z0Xj9Xenp3K7UPHPjGSl1JqktKs1ZbkmoH/F9rtcvKs6zVliQ12HveJWnrF9Ot1a6s3GettiQlJ/ezWj8hoYe12oFAirXakuR59urb793uS6zd+jH79tAu28+7bfHaf2NjTafW44wIAABwhiACAACcIYgAAABnCCIAAMAZgggAAHCGIAIAAJwhiAAAAGcIIgAAwBmCCAAAcIYgAgAAnCGIAAAAZwgiAADAGYIIAABwhiACAACcIYgAAABnCCIAAMAZgggAAHCGIAIAAJwhiAAAAGcIIgAAwBmCCAAAcIYgAgAAnEl03UBrqr97W+ZA0E7x0H47dSXpf7baqy2p25fHW6udk1RurbYkqfsAu+W7N1irnZLyfWu1JSkxMctq/YSE7tZqe16KtdqSFAjYq+95MfsS2CHx3X/89h7fz7s9CQmdO7fBGREAAOAMQQQAADhDEAEAAM4QRAAAgDMEEQAA4AxBBAAAOEMQAQAAzkQdRNauXauxY8cqOztbnudp6dKlrY695ZZb5HmeZs+efQQtAgCArirqIFJXV6dhw4Zpzpw5bY5bsmSJ1q9fr+zs7E43BwAAuraofx6uoKBABQUFbY756quvdPvtt2v58uUaM2ZMp5sDAABdm++/UxsOhzVx4kTdc889Gjx4cLvjGxoa1NDwn5/mrq6u9rslAAAQo3z/sOpjjz2mxMRE3XHHHR0aX1RUpIyMjMiSk5Pjd0sAACBG+RpENm/erN/97ndauHChPM/r0DozZsxQVVVVZCkrK/OzJQAAEMN8DSIffPCBKioqlJubq8TERCUmJmrXrl26++67NWDAgBbXCQaDSk9Pb7YAAIBjg6+fEZk4caLy8/Ob3Td69GhNnDhRkydP9nNTAACgC4g6iNTW1mrnzp2R26Wlpdq6dat69uyp3Nxc9erVq9n4pKQkZWVlaeDAgUfeLQAA6FKiDiKbNm3SqFGjIrenTZsmSZo0aZIWLlzoW2MAAKDrizqIjBw5UsaYDo//xz/+Ee0mAADAMYJrzQAAAGcIIgAAwBmCCAAAcIYgAgAAnPH9WjNH6uAHYWtrG9oZeQRCFmvXHrBXW1LqgbC12vWhemu1JammtslqfWNC1mpXV++zVluSEhPrrNZPSLBX2/PszmsgYK++58XcS2BU4rt/i/8oLYvv592e6uoaSYrqCy2S5Jlo17Dsyy+/5HozAADEqbKyMvXr16/D42MuiITDYe3Zs0dpaWkdul5NdXW1cnJyVFZW1uV/Hp597ZrY166Jfe2ajqV9laLbX2OMampqlJ2drUCg45/8iLnzS4FAIKokddCxdJ0a9rVrYl+7Jva1azqW9lXq+P5mZGREXZsPqwIAAGcIIgAAwJm4DyLBYFCzZs1SMBh03Yp17GvXxL52Texr13Qs7at0dPY35j6sCgAAjh1xf0YEAADEL4IIAABwhiACAACcIYgAAABn4iKIzJkzRwMGDFBKSoqGDx+ujRs3tjn+jTfe0KBBg5SSkqKhQ4fqj3/841HqtPOKiop07rnnKi0tTX369NH48eNVUlLS5joLFy6U53nNlpSUlKPUcefdf//9h/U9aNCgNteJxzmVpAEDBhy2r57nqbCwsMXx8Tana9eu1dixY5WdnS3P87R06dJmjxtjdN9996lv375KTU1Vfn6+duzY0W7daI/5o6GtfW1qatL06dM1dOhQdevWTdnZ2br22mu1Z8+eNmt25lg4Gtqb1+uuu+6wvi+55JJ268bbvEpq8fj1PE9PPPFEqzVjcV478h5TX1+vwsJC9erVS927d9fll1+uvXv3tlm3s8f4f4v5IPLaa69p2rRpmjVrloqLizVs2DCNHj1aFRUVLY7/+OOPdc011+iGG27Qli1bNH78eI0fP17bt28/yp1HZ82aNSosLNT69eu1YsUKNTU16eKLL1ZdXdsXQ0tPT9fXX38dWXbt2nWUOj4ygwcPbtb3hx9+2OrYeJ1TSfrkk0+a7eeKFSskSVdccUWr68TTnNbV1WnYsGGaM2dOi48//vjjevrppzVv3jxt2LBB3bp10+jRo1Vf3/oFFqM95o+WtvZ13759Ki4u1syZM1VcXKw333xTJSUluuyyy9qtG82xcLS0N6+SdMkllzTre/HixW3WjMd5ldRsH7/++mvNnz9fnufp8ssvb7NurM1rR95j7rrrLv3hD3/QG2+8oTVr1mjPnj362c9+1mbdzhzjhzEx7rzzzjOFhYWR26FQyGRnZ5uioqIWx1955ZVmzJgxze4bPny4ufnmm6326beKigojyaxZs6bVMQsWLDAZGRlHrymfzJo1ywwbNqzD47vKnBpjzJ133mlOOukkEw6HW3w8XufUGGMkmSVLlkRuh8Nhk5WVZZ544onIfZWVlSYYDJrFixe3WifaY96FQ/e1JRs3bjSSzK5du1odE+2x4EJL+zpp0iQzbty4qOp0lXkdN26cufDCC9scEw/zeuh7TGVlpUlKSjJvvPFGZMxnn31mJJl169a1WKOzx/ihYvqMSGNjozZv3qz8/PzIfYFAQPn5+Vq3bl2L66xbt67ZeEkaPXp0q+NjVVVVlSSpZ8+ebY6rra1V//79lZOTo3HjxunTTz89Gu0dsR07dig7O1snnniiJkyYoN27d7c6tqvMaWNjo1566SVdf/31bV7QMV7n9FClpaUqLy9vNncZGRkaPnx4q3PXmWM+VlVVVcnzPPXo0aPNcdEcC7Fk9erV6tOnjwYOHKhbb71V3377batju8q87t27V++++65uuOGGdsfG+rwe+h6zefNmNTU1NZujQYMGKTc3t9U56swx3pKYDiLffPONQqGQMjMzm92fmZmp8vLyFtcpLy+PanwsCofDmjp1qi644AINGTKk1XEDBw7U/Pnz9dZbb+mll15SOBzW+eefry+//PIodhu94cOHa+HChVq2bJnmzp2r0tJS/fCHP1RNTU2L47vCnErS0qVLVVlZqeuuu67VMfE6py05OD/RzF1njvlYVF9fr+nTp+uaa65p80Jh0R4LseKSSy7Riy++qJUrV+qxxx7TmjVrVFBQoFAo1OL4rjKvixYtUlpaWrt/roj1eW3pPaa8vFzJycmHBef23m8PjunoOi2JuavvQiosLNT27dvb/ZviiBEjNGLEiMjt888/X6eeeqqee+45PfTQQ7bb7LSCgoLIf59++ukaPny4+vfvr9dff71D/6cRr1544QUVFBQoOzu71THxOqf4j6amJl155ZUyxmju3Lltjo3XY+Hqq6+O/PfQoUN1+umn66STTtLq1at10UUXOezMrvnz52vChAntfoA81ue1o+8xR0tMnxHp3bu3EhISDvvU7t69e5WVldXiOllZWVGNjzVTpkzRO++8o1WrVqlfv35RrZuUlKQzzzxTO3futNSdHT169NApp5zSat/xPqeStGvXLr333nv65S9/GdV68TqnkiLzE83cdeaYjyUHQ8iuXbu0YsWKqC8T396xEKtOPPFE9e7du9W+431eJemDDz5QSUlJ1MewFFvz2tp7TFZWlhobG1VZWdlsfHvvtwfHdHSdlsR0EElOTtbZZ5+tlStXRu4Lh8NauXJls/9r/G8jRoxoNl6SVqxY0er4WGGM0ZQpU7RkyRK9//77ysvLi7pGKBTStm3b1LdvXwsd2lNbW6svvvii1b7jdU7/24IFC9SnTx+NGTMmqvXidU4lKS8vT1lZWc3mrrq6Whs2bGh17jpzzMeKgyFkx44deu+999SrV6+oa7R3LMSqL7/8Ut9++22rfcfzvB70wgsv6Oyzz9awYcOiXjcW5rW995izzz5bSUlJzeaopKREu3fvbnWOOnOMt9ZcTHv11VdNMBg0CxcuNH/961/NTTfdZHr06GHKy8uNMcZMnDjR3HvvvZHxH330kUlMTDRPPvmk+eyzz8ysWbNMUlKS2bZtm6td6JBbb73VZGRkmNWrV5uvv/46suzbty8y5tB9feCBB8zy5cvNF198YTZv3myuvvpqk5KSYj799FMXu9Bhd999t1m9erUpLS01H330kcnPzze9e/c2FRUVxpiuM6cHhUIhk5uba6ZPn37YY/E+pzU1NWbLli1my5YtRpJ56qmnzJYtWyLfFHn00UdNjx49zFtvvWX+8pe/mHHjxpm8vDyzf//+SI0LL7zQPPPMM5Hb7R3zrrS1r42Njeayyy4z/fr1M1u3bm12DDc0NERqHLqv7R0LrrS1rzU1NeZXv/qVWbdunSktLTXvvfeeOeuss8zJJ59s6uvrIzW6wrweVFVVZY477jgzd+7cFmvEw7x25D3mlltuMbm5ueb99983mzZtMiNGjDAjRoxoVmfgwIHmzTffjNzuyDHenpgPIsYY88wzz5jc3FyTnJxszjvvPLN+/frIYz/+8Y/NpEmTmo1//fXXzSmnnGKSk5PN4MGDzbvvvnuUO46epBaXBQsWRMYcuq9Tp06NPC+ZmZnmJz/5iSkuLj76zUfpqquuMn379jXJycnme9/7nrnqqqvMzp07I493lTk9aPny5UaSKSkpOeyxeJ/TVatWtfjv9uA+hcNhM3PmTJOZmWmCwaC56KKLDnse+vfvb2bNmtXsvraOeVfa2tfS0tJWj+FVq1ZFahy6r+0dC660ta/79u0zF198sTnhhBNMUlKS6d+/v7nxxhsPCxRdYV4Peu6550xqaqqprKxssUY8zGtH3mP2799vbrvtNnP88ceb4447zvz0pz81X3/99WF1/nudjhzj7fH+XRgAAOCoi+nPiAAAgK6NIAIAAJwhiAAAAGcIIgAAwBmCCAAAcIYgAgAAnCGIAAAAZwgiAADAGYIIAABwhiACAACcIYgAAABnCCIAAMCZ/w8pqNUcCKL34wAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from numpy import array\n",
    "ffts = array(ffts)\n",
    "plt.imshow(abs(ffts), cmap=cmap)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "36d4e36f-e606-494c-968f-ab6583998be0",
   "metadata": {},
   "source": [
    "### Range Doppler FFT on cube\n",
    "\n",
    "> 2nd FFT on 2D cube shows one static target and one moving\n",
    "\n",
    "> similarly as to a 2D FFT would."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "9ed9d214",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x282aea06850>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fft2 = fft(ffts, axis=0)\n",
    "plt.imshow(abs(fft2), cmap=cmap)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "01142773-effe-471b-ad35-8fe886ae3e97",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}