RADAR.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Radar FMCW and CSM algorithms\n",
    "\n",
    "This notebook shows a naive (didactically intuitive) implementation of following algorithms:\n",
    "\n",
    "- FMCW (Frequency Modulated Continuous Wave)\n",
    "- CSM (Chirp Sequence Modulation)\n",
    "\n",
    "Both algorithms are used for range and velocity measurements in automated/assisted driving domain."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Introduction\n",
    "\n",
    "### Doppler\n",
    "\n",
    "An electromagnetic wave \n",
    "\n",
    "\\begin{align}\n",
    "w(t) &= a_t cos(2\\pi f_0t)\n",
    "\\end{align}\n",
    "\n",
    "reflected on a moving object with velocity $v$ leads to a new wave:\n",
    "\n",
    "\\begin{align}\n",
    "u_r(t) &= a_r \\text{cos}(2\\pi (f_0 - f_{d}) t + \\phi_r + \\phi_t) \\\\\n",
    "\n",
    "\\end{align}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In order to understand what signal the algorithms operate on we have to take a closer look at the inner workings of a continuous wave radar (simplified view):\n",
    "\n",
    "![cw-radar](cw-radar.png)\n",
    "\n",
    "[Source](https://en.wikipedia.org/wiki/Continuous-wave_radar#/media/File:Bsp2_CW-Radar.EN.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Antennas\n",
    "\n",
    "The CW-RADAR has one transmitting antenna and at least one receiving antenna. The former emits a continuous radio wave, that's different to pulse-based RADAR systems. The receiving antenna transforms the reflected waves from the object of interests and converts the signal into eletrical domain (voltage).\n",
    "\n",
    "Automotive long range radars use a $77.7\\text{GHz}$ base frequency.\n",
    "\n",
    "### RF-Generator\n",
    "\n",
    "The RF-generator is a module which dynamically generates a sine voltage with a particular frequency. Since both methods presented here modulate (alter) the frequency of the tramitted radio wave, the generator is an essential part in the system.\n",
    "\n",
    "### Mixer\n",
    "\n",
    "The mixer is the most important component in the system described here. It allows us to measure the frequency change introduced by the moving object we are going to detect. We apply to the antenna the voltage $u_t(t)$ and receive the voltage $u_r(t)$.\n",
    "\n",
    "\\begin{align}\n",
    "u_t(t) &= A_t \\text{cos}(2\\pi f_0 t+\\phi_t) \\\\\n",
    "u_r(t) &= A_r \\text{cos}(2\\pi (f_0 - f_{d}) t + \\phi_r)\n",
    "\\end{align}\n",
    "\n",
    "With Doppler frequency\n",
    "\n",
    "\\begin{align}\n",
    "f_{d} = \\frac{2v}{\\lambda} = \\frac{2 \\dot r}{\\lambda} = \\frac{2 f_0 \\dot r}{c}\n",
    "\\end{align}\n",
    "\n",
    "Given base wavelength $\\lambda$ and target velocity $v=\\dot r$.\n",
    "\n",
    "Theoretically, if we could sample $f_0 - f_{d} \\approx 77.7GHz$ and we were done. But high frequency AD converters (according to Nyquist $\\geq 2f_0 \\approx 145GHz$ is required) are techinically expensive and the change introduced by $f_d$ is very small to detect changes. That's why we need the mixer to get rid of the high frequency $f_0$ and work only on the $f_d$. \n",
    "\n",
    "The mixer multiplies both signals, corresponding to trigonometry relations:\n",
    "\n",
    "\\begin{align}\n",
    "\\text{cos}(x)\\text{cos}(y) = \\frac{1}{2} [ \\text{cos}(x-y) + \\text{cos}(x+y)]\n",
    "\\end{align}\n",
    "\n",
    "Applied to $u_t(t)$ and $u_r(t)$:\n",
    "\n",
    "\\begin{align}\n",
    "u_t(t)u_r(t) &= \\frac{A_t A_r}{2} [ \\text{cos}(2\\pi f_0 t+\\phi_t-2\\pi (f_0 - f_{d}) t - \\phi_r) + \\text{cos}(2\\pi f_0 t+\\phi_t+ 2\\pi (f_0 - f_{d}) t + \\phi_r)] \\\\\n",
    "&= \\frac{A_t A_r}{2} [ \\text{cos}(2\\pi f_{d} t + \\phi_t - \\phi_r) + \\text{cos}(2\\pi f_0 t+\\phi_t + 2\\pi (f_0- f_{d}) t + \\phi_r)] \\\\\n",
    "&= \\frac{A_t A_r}{2} [ \\text{cos}(2\\pi f_{d} t + \\phi_t - \\phi_r) + \\text{cos}(2\\pi \\underbrace{2 f_0}_{\\text{2x 77GHz}} t - 2\\pi f_{d}t + \\phi_t + \\phi_r)] \\\\\n",
    "\\end{align}\n",
    "\n",
    "The product of both signals equals to a sum of two waves, the first, only dependent on the doppler frequency (which is velocity dependent) and the second a very high frequency signal (144 GHz) which we filter out with the low pass filter:\n",
    "\n",
    "\\begin{align}\n",
    "u_{It,r}(t) = \\frac{A_t A_r}{2} \\text{cos}(2\\pi f_{d} t + \\phi_t - \\phi_r)\n",
    "\\end{align}\n",
    "\n",
    "After the AD converter we could sample $u_{It,r}(t)$ and measure the (unsigned) velocity. The index $I$ means in-phase. We later will introduce an other index in order to extract the sign of the velocity (approaching vs. departing)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "import platform"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sys.version_info(major=3, minor=10, micro=11, releaselevel='final', serial=0)\n",
      "arm64\n"
     ]
    }
   ],
   "source": [
    "print(sys.version_info)\n",
    "print(platform.machine())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "from scipy.fftpack import fft"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Constant for velocity of light within the air:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "c = 299792458"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## FCMW\n",
    "\n",
    "Instead of sending with one frequency, we will alter $f_0$ over time:\n",
    "\n",
    "\\begin{align}\n",
    "u_t(t) &= A_t \\text{cos}(2\\pi f_t t+\\phi_t)\n",
    "\\end{align}\n",
    "\n",
    "with \n",
    "\n",
    "\\begin{align}\n",
    "f_t = f_t(t) = f_0 + m_w(t-t_0)\n",
    "\\end{align}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "f_0 = 77.7*1e9 # 77.7GHz\n",
    "\n",
    "phi_t = 0\n",
    "A_t = 1\n",
    "f_ramp = 425*1e6 #Hz\n",
    "T_ramp = 0.010\n",
    "m_w = f_ramp/T_ramp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def f_t(t):\n",
    "    return f_0 + m_w*(t % T_ramp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def u_t(t):\n",
    "    f_t = f_t(t)\n",
    "    return A_t*np.cos(2*np.pi*f_b*t + phi_t)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The received signal depends on both the range $r$ and the velocity $v$:\n",
    "\n",
    "\\begin{align}\n",
    "u_r(t) &= A_r \\text{cos}(2\\pi f_r t+\\phi_r)\n",
    "\\end{align}\n",
    "\n",
    "with \n",
    "\n",
    "\\begin{align}\n",
    "f_r = f_r(t) = f_0 + m_w(t- \\frac{2r}{c}-t_0) - \\frac{2vf_0}{c}\n",
    "\\end{align}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "v = 50/3.6 # 50km/h\n",
    "r = 100 # 100m distance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def f_r(t):\n",
    "    return f_0 + m_w*(t % T_ramp - 2*r/c) - 2*v*f_0/c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "t = np.arange(0, 2*T_ramp, 1e-8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,5))\n",
    "plt.plot(t, f_t(t), label=\"$f_t$\")\n",
    "plt.plot(t, f_r(t), label=\"$f_r$\")\n",
    "plt.legend()\n",
    "plt.xlabel(\"t [s]\")\n",
    "plt.ylabel(\"frequency [Hz]\")\n",
    "plt.title(\"Transmitted and received frequencies\")\n",
    "plt.grid();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Because we don't see any difference let's zoom in "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "t_op = T_ramp\n",
    "plt.figure(figsize=(10,10))\n",
    "plt.plot(t, f_t(t), label=\"$f_t$\")\n",
    "plt.plot(t, f_r(t), label=\"$f_r$\")\n",
    "plt.legend()\n",
    "plt.xlim([t_op-T_ramp/10000, t_op+T_ramp/10000])\n",
    "plt.ylim([f_0-100e3, f_0+100e3])\n",
    "plt.xlabel(\"t [s]\")\n",
    "plt.ylabel(\"frequency [Hz]\")\n",
    "plt.title(\"Transmitted and received frequencies\")\n",
    "plt.grid();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If we could measure $\\Delta f$ directly we could derive $r$ and $v$:\n",
    "\n",
    "\\begin{align}\n",
    "\\Delta f = f_t-f_r = \\frac{2m_w}{c}r + \\frac{2 f_0}{c}\\dot r\n",
    "\\end{align}\n",
    "\n",
    "There is just one problem. We have one equation but two unknowns. The solution for that problem is to have a second ramp with a different $m_w$:\n",
    "\n",
    "\\begin{align}\n",
    "f_t(t) = \\{\\begin{array}{lr}\n",
    "        f_0 + m_{w,1}(t-t_0), & \\text{for } 0 \\leq t < T_{r,1}\\\\\n",
    "        f_0 + m_w T_{r,1} + m_{w,2}(t-t_0), & \\text{for } T_{r,1} \\leq t < T_{r,1}+T_{r,2}\\\n",
    "        \\end{array}\n",
    "\\end{align}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Define and implement both waveforms:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "T_ramp1 = T_ramp*0.7\n",
    "T_ramp2 = T_ramp*0.3\n",
    "m_w1 = f_ramp/T_ramp1\n",
    "m_w2 = -f_ramp/T_ramp2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "def f_t(t):\n",
    "    r1 = f_0 + m_w1*(t % (T_ramp1+T_ramp2))\n",
    "    r1[(t%(T_ramp1+T_ramp2)) > T_ramp1] = 0\n",
    "    \n",
    "    r2 = f_0 + m_w1*T_ramp1 + m_w2*( (t-T_ramp1) % (T_ramp1+T_ramp2))\n",
    "    r2[(t%(T_ramp1+T_ramp2)) <= T_ramp1] = 0\n",
    "    \n",
    "    return r1+r2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "def f_r(t):\n",
    "    r1 = f_0 + m_w1*(t % (T_ramp1+T_ramp2) - 2*r/c) - 2*v*f_0/c\n",
    "    r1[(t%(T_ramp1+T_ramp2)) > T_ramp1] = 0\n",
    "    \n",
    "    r2 = f_0 + m_w1*T_ramp1 + m_w2*( (t-T_ramp1) % (T_ramp1+T_ramp2) - 2*r/c) - 2*v*f_0/c\n",
    "    r2[(t%(T_ramp1+T_ramp2)) <= T_ramp1] = 0\n",
    "    return r1+r2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "t = np.arange(0, 2*T_ramp, 1e-7)\n",
    "plt.figure(figsize=(15,5))\n",
    "plt.plot(t, f_t(t), label=\"$f_t$\")\n",
    "plt.plot(t, f_r(t), label=\"$f_r$\")\n",
    "plt.legend()\n",
    "plt.xlabel(\"t [s]\")\n",
    "plt.ylabel(\"frequency [Hz]\")\n",
    "plt.title(\"FMCW ramps with different $m_{w,1} \\\\neq m_{w,2}$\")\n",
    "plt.grid();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Zoom in again:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "t_op = T_ramp\n",
    "plt.figure(figsize=(10,5))\n",
    "plt.plot(t, f_t(t), label=\"$f_t$\")\n",
    "plt.plot(t, f_r(t), label=\"$f_r$\")\n",
    "plt.legend()\n",
    "plt.xlim([t_op-T_ramp/5000, t_op+T_ramp/5000])\n",
    "plt.ylim([f_0-100e3, f_0+600e3])\n",
    "plt.xlabel(\"t [s]\")\n",
    "plt.ylabel(\"frequency [Hz]\")\n",
    "plt.title(\"FMCW ramps with different $m_{w,1} \\\\neq m_{w,2}$\")\n",
    "plt.grid();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we have two equations:\n",
    "\n",
    "\\begin{align}\n",
    "\\Delta f_1 = \\frac{2m_{w,1}}{c}r + \\frac{2 f_0}{c}\\dot r \\\\\n",
    "\\Delta f_2 = \\frac{2m_{w,2}}{c}r + \\frac{2 f_0}{c}\\dot r\n",
    "\\end{align}\n",
    "\n",
    "Solving the equation system:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "t_f1 = np.asarray([T_ramp*0.1]) # beginning of rising ramp\n",
    "t_f2 = np.asarray([T_ramp*0.8])  # beginning of falling ramp\n",
    "delta_f_1 = f_t(t_f1) - f_r(t_f1)\n",
    "delta_f_2 = f_t(t_f2) - f_r(t_f2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "A = np.asarray([[2*m_w1/c, 2*f_0/c], [2*m_w2/c, 2*f_0/c]])\n",
    "Y = np.asarray([delta_f_1, delta_f_2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "range r: 99.99999999693145\n",
      "velocity v: 49.999999885084705\n"
     ]
    }
   ],
   "source": [
    "x = np.linalg.solve(A, Y).flatten()\n",
    "print(\"range r:\", x[0])\n",
    "print(\"velocity v:\", x[1]*3.6)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you could see we could successfully estimate the range and velocity."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Note**: we get $\\Delta f_i$ for free as a result of the FFT on the mixed and filtered signal \n",
    "\n",
    "\n",
    "\\begin{align}\n",
    "u_{It,r}(t) = \\frac{A_t A_r}{2} \\text{cos}(2\\pi (f_t - f_r) t + \\phi_t - \\phi_r) = \\frac{A_t A_r}{2} \\text{cos}(2\\pi \\Delta f t + \\phi_t - \\phi_r)\n",
    "\\end{align}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the FMCW chapter we did not address various problems like:\n",
    "\n",
    "- multi target estimation (what happens if the FFT returns 2, 3, 4, ... major peaks?)\n",
    "- angle estimation\n",
    "\n",
    "We will solve the first problem in our second method."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Chirp Sequence Modulation\n",
    "\n",
    "This method is an extension of FMCW. Instead of sending one singe rising and falling frequency chirp we will repeat that process $n_r$ times in a sequence with chirp frequency $f_{chirp}$:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# chirp sequence frequency\n",
    "f_chirp = 50*1e3 #Hz\n",
    "\n",
    "# ramp frequency\n",
    "f_r = 200*1e6 #Hz\n",
    "T_r = 1/f_chirp # duration of one cycle\n",
    "m_w = f_r/T_r\n",
    "\n",
    "n_r = 150 # number of chirps\n",
    "T_M = T_r*n_r"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Because we perform analog sampling, we have to configure our AD-converter:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# sample settings\n",
    "f_s = 50e6 #50 MHz\n",
    "n_s = int(T_r*f_s)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Base frequency setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "f_0 = 77.7*1e9\n",
    "\n",
    "# some helpful\n",
    "w_0 = 2*np.pi*f_0\n",
    "lambda_0 = c/f_0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "def f_transmitted(t):\n",
    "    return f_0 + m_w*(t%T_r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "def chirp(t):\n",
    "    return np.cos(2*np.pi*(f_transmitted(t))*t)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Lets visualize the chirp sequence:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "t = np.linspace(0, 3*T_r, int(1e6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,5))\n",
    "plt.plot(t, f_transmitted(t))\n",
    "plt.xlabel(\"t [s]\")\n",
    "plt.ylabel(\"frequency [Hz]\")\n",
    "plt.title(\"Chirp sequence Modulation, transmitted signal $f_t(t)$\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Reflector setup \n",
    "\n",
    "This is our target of interest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "r_0 = 50 # initial distance\n",
    "v_veh = 36/3.6 # velocity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_range(t):\n",
    "    return r_0+v_veh*t"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Returned waveform\n",
    "\n",
    "According to Eq. 17.46 in [1](https://www.springer.com/de/book/9783658057336) the returned waveform (after mixing and LF-filter) is:\n",
    "\n",
    "\\begin{align}\n",
    "u_{It,r}(t) = \\frac{A_t A_r}{2} \\text{cos}\\left(2\\pi(\\frac{2m_w}{c}r + \\frac{2 f_0}{c}\\dot r)t + \\frac{4 \\pi f_0 r}{c} + 2\\pi(\\frac{2 r}{c})^2m_w\\right)\n",
    "\\end{align}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(325694.31641129137, 27.963945936914552)"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "4*np.pi*100*f_0/c, 2*np.pi*(2*100/c)**2*m_w"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you can see $2\\pi(\\frac{2 r}{c})^2m_w$ has not so much influence on the phase, so we ignore it:\n",
    "\n",
    "\\begin{align}\n",
    "u_{It,r}(t) = \\frac{A_t A_r}{2} \\text{cos}\\left(2\\pi(\\frac{2m_w}{c}r + \\frac{2 f_0}{c}\\dot r)t + \\frac{4 \\pi f_0 r}{c}\\right)\n",
    "\\end{align}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "def itr(t):\n",
    "    r = get_range(t)\n",
    "    w_itr = 2*f_0*v_veh/c + 2*m_w*r/c\n",
    "    # we do t%T_r because the eq. above only valid within the ramp\n",
    "    v = np.cos(2*np.pi*w_itr*(t%T_r) +2*r*2*np.pi*f_0/c)\n",
    "    return v"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We build up a table of $n_r × n_s$ where $n_r$ is the number of chirps (ramps) and $n_s$ is the number of samples within a chirp."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "150 1000\n"
     ]
    }
   ],
   "source": [
    "print(n_r, n_s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "t_sample = np.linspace(0, T_M, n_r*n_s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "v_sample = itr(t_sample)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,5))\n",
    "plt.plot(t_sample, v_sample, \"+\")\n",
    "plt.xlim(0, 0.1*T_r)\n",
    "plt.xlabel(\"t [s]\")\n",
    "plt.title(\"Samples visualized in time range [0, 10% $T_r$]\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We allocate memory for the sampling data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "table = np.zeros((n_r, n_s))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Fill in the values ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "for chirp_nr in range(n_r):\n",
    "    table[chirp_nr, :] = v_sample[(chirp_nr*n_s):(n_s*(chirp_nr+1))]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "DF for pretty printing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "table_df = pd.DataFrame(data=table, \n",
    "                        columns=[\"sample_%03d\"%i for i in range(n_s)], \n",
    "                        index=[\"chirp_%03d\"%i for i in range(n_r)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sample_000</th>\n",
       "      <th>sample_001</th>\n",
       "      <th>sample_002</th>\n",
       "      <th>sample_003</th>\n",
       "      <th>sample_004</th>\n",
       "      <th>sample_005</th>\n",
       "      <th>sample_006</th>\n",
       "      <th>sample_007</th>\n",
       "      <th>sample_008</th>\n",
       "      <th>sample_009</th>\n",
       "      <th>...</th>\n",
       "      <th>sample_990</th>\n",
       "      <th>sample_991</th>\n",
       "      <th>sample_992</th>\n",
       "      <th>sample_993</th>\n",
       "      <th>sample_994</th>\n",
       "      <th>sample_995</th>\n",
       "      <th>sample_996</th>\n",
       "      <th>sample_997</th>\n",
       "      <th>sample_998</th>\n",
       "      <th>sample_999</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>chirp_000</th>\n",
       "      <td>0.905353</td>\n",
       "      <td>0.999836</td>\n",
       "      <td>0.920138</td>\n",
       "      <td>0.680144</td>\n",
       "      <td>0.321662</td>\n",
       "      <td>-0.092857</td>\n",
       "      <td>-0.491199</td>\n",
       "      <td>-0.803969</td>\n",
       "      <td>-0.976681</td>\n",
       "      <td>-0.979245</td>\n",
       "      <td>...</td>\n",
       "      <td>0.415170</td>\n",
       "      <td>0.007652</td>\n",
       "      <td>-0.401199</td>\n",
       "      <td>-0.740157</td>\n",
       "      <td>-0.950170</td>\n",
       "      <td>-0.994652</td>\n",
       "      <td>-0.865854</td>\n",
       "      <td>-0.586214</td>\n",
       "      <td>-0.204448</td>\n",
       "      <td>0.212936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chirp_001</th>\n",
       "      <td>0.976847</td>\n",
       "      <td>0.804429</td>\n",
       "      <td>0.491871</td>\n",
       "      <td>0.093624</td>\n",
       "      <td>-0.320933</td>\n",
       "      <td>-0.679581</td>\n",
       "      <td>-0.919838</td>\n",
       "      <td>-0.999850</td>\n",
       "      <td>-0.905677</td>\n",
       "      <td>-0.653725</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.225759</td>\n",
       "      <td>-0.603753</td>\n",
       "      <td>-0.876566</td>\n",
       "      <td>-0.996670</td>\n",
       "      <td>-0.943140</td>\n",
       "      <td>-0.725302</td>\n",
       "      <td>-0.381107</td>\n",
       "      <td>0.029482</td>\n",
       "      <td>0.434935</td>\n",
       "      <td>0.764616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chirp_002</th>\n",
       "      <td>0.644981</td>\n",
       "      <td>0.276856</td>\n",
       "      <td>-0.139501</td>\n",
       "      <td>-0.531555</td>\n",
       "      <td>-0.831006</td>\n",
       "      <td>-0.985685</td>\n",
       "      <td>-0.968646</td>\n",
       "      <td>-0.782858</td>\n",
       "      <td>-0.460686</td>\n",
       "      <td>-0.058257</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.773011</td>\n",
       "      <td>-0.964635</td>\n",
       "      <td>-0.988205</td>\n",
       "      <td>-0.839616</td>\n",
       "      <td>-0.544753</td>\n",
       "      <td>-0.154986</td>\n",
       "      <td>0.261782</td>\n",
       "      <td>0.632944</td>\n",
       "      <td>0.893837</td>\n",
       "      <td>0.999011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chirp_003</th>\n",
       "      <td>0.046790</td>\n",
       "      <td>-0.365037</td>\n",
       "      <td>-0.713270</td>\n",
       "      <td>-0.937241</td>\n",
       "      <td>-0.997932</td>\n",
       "      <td>-0.884770</td>\n",
       "      <td>-0.617469</td>\n",
       "      <td>-0.242597</td>\n",
       "      <td>0.174539</td>\n",
       "      <td>0.561268</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.999508</td>\n",
       "      <td>-0.925246</td>\n",
       "      <td>-0.689792</td>\n",
       "      <td>-0.334165</td>\n",
       "      <td>0.079680</td>\n",
       "      <td>0.479643</td>\n",
       "      <td>0.796044</td>\n",
       "      <td>0.973761</td>\n",
       "      <td>0.981834</td>\n",
       "      <td>0.818855</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chirp_004</th>\n",
       "      <td>-0.570722</td>\n",
       "      <td>-0.856199</td>\n",
       "      <td>-0.992513</td>\n",
       "      <td>-0.955916</td>\n",
       "      <td>-0.752785</td>\n",
       "      <td>-0.418507</td>\n",
       "      <td>-0.011319</td>\n",
       "      <td>0.397840</td>\n",
       "      <td>0.737690</td>\n",
       "      <td>0.949024</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.811267</td>\n",
       "      <td>-0.501932</td>\n",
       "      <td>-0.105152</td>\n",
       "      <td>0.309948</td>\n",
       "      <td>0.671049</td>\n",
       "      <td>0.915242</td>\n",
       "      <td>0.999983</td>\n",
       "      <td>0.910510</td>\n",
       "      <td>0.662410</td>\n",
       "      <td>0.298907</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chirp_005</th>\n",
       "      <td>-0.952571</td>\n",
       "      <td>-0.993817</td>\n",
       "      <td>-0.861923</td>\n",
       "      <td>-0.579868</td>\n",
       "      <td>-0.196791</td>\n",
       "      <td>0.220570</td>\n",
       "      <td>0.599505</td>\n",
       "      <td>0.873996</td>\n",
       "      <td>0.996222</td>\n",
       "      <td>0.944891</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.286397</td>\n",
       "      <td>0.129656</td>\n",
       "      <td>0.523121</td>\n",
       "      <td>0.825448</td>\n",
       "      <td>0.983966</td>\n",
       "      <td>0.971059</td>\n",
       "      <td>0.788975</td>\n",
       "      <td>0.469436</td>\n",
       "      <td>0.068113</td>\n",
       "      <td>-0.345076</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chirp_006</th>\n",
       "      <td>-0.941085</td>\n",
       "      <td>-0.721066</td>\n",
       "      <td>-0.375424</td>\n",
       "      <td>0.035623</td>\n",
       "      <td>0.440464</td>\n",
       "      <td>0.768568</td>\n",
       "      <td>0.962774</td>\n",
       "      <td>0.989248</td>\n",
       "      <td>0.843378</td>\n",
       "      <td>0.550576</td>\n",
       "      <td>...</td>\n",
       "      <td>0.357312</td>\n",
       "      <td>0.707445</td>\n",
       "      <td>0.934326</td>\n",
       "      <td>0.998429</td>\n",
       "      <td>0.888586</td>\n",
       "      <td>0.623932</td>\n",
       "      <td>0.250578</td>\n",
       "      <td>-0.166433</td>\n",
       "      <td>-0.554448</td>\n",
       "      <td>-0.845866</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chirp_007</th>\n",
       "      <td>-0.541005</td>\n",
       "      <td>-0.150571</td>\n",
       "      <td>0.266096</td>\n",
       "      <td>0.636404</td>\n",
       "      <td>0.895838</td>\n",
       "      <td>0.999200</td>\n",
       "      <td>0.928483</td>\n",
       "      <td>0.696006</td>\n",
       "      <td>0.342272</td>\n",
       "      <td>-0.071093</td>\n",
       "      <td>...</td>\n",
       "      <td>0.852756</td>\n",
       "      <td>0.991682</td>\n",
       "      <td>0.957836</td>\n",
       "      <td>0.757114</td>\n",
       "      <td>0.424486</td>\n",
       "      <td>0.017904</td>\n",
       "      <td>-0.391798</td>\n",
       "      <td>-0.733240</td>\n",
       "      <td>-0.946936</td>\n",
       "      <td>-0.995655</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chirp_008</th>\n",
       "      <td>0.082467</td>\n",
       "      <td>0.482098</td>\n",
       "      <td>0.797739</td>\n",
       "      <td>0.974397</td>\n",
       "      <td>0.981296</td>\n",
       "      <td>0.817232</td>\n",
       "      <td>0.510791</td>\n",
       "      <td>0.115359</td>\n",
       "      <td>-0.300171</td>\n",
       "      <td>-0.663405</td>\n",
       "      <td>...</td>\n",
       "      <td>0.994356</td>\n",
       "      <td>0.864427</td>\n",
       "      <td>0.583895</td>\n",
       "      <td>0.201635</td>\n",
       "      <td>-0.215755</td>\n",
       "      <td>-0.595555</td>\n",
       "      <td>-0.871595</td>\n",
       "      <td>-0.995784</td>\n",
       "      <td>-0.946484</td>\n",
       "      <td>-0.732285</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chirp_009</th>\n",
       "      <td>0.671886</td>\n",
       "      <td>0.915698</td>\n",
       "      <td>0.999976</td>\n",
       "      <td>0.910036</td>\n",
       "      <td>0.661548</td>\n",
       "      <td>0.297805</td>\n",
       "      <td>-0.117823</td>\n",
       "      <td>-0.512924</td>\n",
       "      <td>-0.818662</td>\n",
       "      <td>-0.981771</td>\n",
       "      <td>...</td>\n",
       "      <td>0.723355</td>\n",
       "      <td>0.378482</td>\n",
       "      <td>-0.032331</td>\n",
       "      <td>-0.437512</td>\n",
       "      <td>-0.766468</td>\n",
       "      <td>-0.961886</td>\n",
       "      <td>-0.989720</td>\n",
       "      <td>-0.845120</td>\n",
       "      <td>-0.553281</td>\n",
       "      <td>-0.165046</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 1000 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           sample_000  sample_001  sample_002  sample_003  sample_004  \\\n",
       "chirp_000    0.905353    0.999836    0.920138    0.680144    0.321662   \n",
       "chirp_001    0.976847    0.804429    0.491871    0.093624   -0.320933   \n",
       "chirp_002    0.644981    0.276856   -0.139501   -0.531555   -0.831006   \n",
       "chirp_003    0.046790   -0.365037   -0.713270   -0.937241   -0.997932   \n",
       "chirp_004   -0.570722   -0.856199   -0.992513   -0.955916   -0.752785   \n",
       "chirp_005   -0.952571   -0.993817   -0.861923   -0.579868   -0.196791   \n",
       "chirp_006   -0.941085   -0.721066   -0.375424    0.035623    0.440464   \n",
       "chirp_007   -0.541005   -0.150571    0.266096    0.636404    0.895838   \n",
       "chirp_008    0.082467    0.482098    0.797739    0.974397    0.981296   \n",
       "chirp_009    0.671886    0.915698    0.999976    0.910036    0.661548   \n",
       "\n",
       "           sample_005  sample_006  sample_007  sample_008  sample_009  ...  \\\n",
       "chirp_000   -0.092857   -0.491199   -0.803969   -0.976681   -0.979245  ...   \n",
       "chirp_001   -0.679581   -0.919838   -0.999850   -0.905677   -0.653725  ...   \n",
       "chirp_002   -0.985685   -0.968646   -0.782858   -0.460686   -0.058257  ...   \n",
       "chirp_003   -0.884770   -0.617469   -0.242597    0.174539    0.561268  ...   \n",
       "chirp_004   -0.418507   -0.011319    0.397840    0.737690    0.949024  ...   \n",
       "chirp_005    0.220570    0.599505    0.873996    0.996222    0.944891  ...   \n",
       "chirp_006    0.768568    0.962774    0.989248    0.843378    0.550576  ...   \n",
       "chirp_007    0.999200    0.928483    0.696006    0.342272   -0.071093  ...   \n",
       "chirp_008    0.817232    0.510791    0.115359   -0.300171   -0.663405  ...   \n",
       "chirp_009    0.297805   -0.117823   -0.512924   -0.818662   -0.981771  ...   \n",
       "\n",
       "           sample_990  sample_991  sample_992  sample_993  sample_994  \\\n",
       "chirp_000    0.415170    0.007652   -0.401199   -0.740157   -0.950170   \n",
       "chirp_001   -0.225759   -0.603753   -0.876566   -0.996670   -0.943140   \n",
       "chirp_002   -0.773011   -0.964635   -0.988205   -0.839616   -0.544753   \n",
       "chirp_003   -0.999508   -0.925246   -0.689792   -0.334165    0.079680   \n",
       "chirp_004   -0.811267   -0.501932   -0.105152    0.309948    0.671049   \n",
       "chirp_005   -0.286397    0.129656    0.523121    0.825448    0.983966   \n",
       "chirp_006    0.357312    0.707445    0.934326    0.998429    0.888586   \n",
       "chirp_007    0.852756    0.991682    0.957836    0.757114    0.424486   \n",
       "chirp_008    0.994356    0.864427    0.583895    0.201635   -0.215755   \n",
       "chirp_009    0.723355    0.378482   -0.032331   -0.437512   -0.766468   \n",
       "\n",
       "           sample_995  sample_996  sample_997  sample_998  sample_999  \n",
       "chirp_000   -0.994652   -0.865854   -0.586214   -0.204448    0.212936  \n",
       "chirp_001   -0.725302   -0.381107    0.029482    0.434935    0.764616  \n",
       "chirp_002   -0.154986    0.261782    0.632944    0.893837    0.999011  \n",
       "chirp_003    0.479643    0.796044    0.973761    0.981834    0.818855  \n",
       "chirp_004    0.915242    0.999983    0.910510    0.662410    0.298907  \n",
       "chirp_005    0.971059    0.788975    0.469436    0.068113   -0.345076  \n",
       "chirp_006    0.623932    0.250578   -0.166433   -0.554448   -0.845866  \n",
       "chirp_007    0.017904   -0.391798   -0.733240   -0.946936   -0.995655  \n",
       "chirp_008   -0.595555   -0.871595   -0.995784   -0.946484   -0.732285  \n",
       "chirp_009   -0.961886   -0.989720   -0.845120   -0.553281   -0.165046  \n",
       "\n",
       "[10 rows x 1000 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "table_df.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now our table consists all sampled measurement during a cycle. We will use this matrix to calculate range and velocity."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### FFT over the first chirp"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For didactic reasons we do the FFT procedure only for the first churp to make an example of the procedure."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "chirp0_samples = table_df.iloc[0].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "chirp0_magnitude = fft(chirp0_samples)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "# frequencies found by FFT, will be used later\n",
    "frequencies = np.arange(0, n_s//2)*f_s/n_s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([     0.,  50000., 100000.])"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frequencies[:3]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Each frequency is referred to a range\n",
    "\n",
    "\\begin{align}\n",
    "f_* = \\frac{2m_w}{c}r + \\frac{2 f_0}{c}\\dot r\n",
    "\\end{align}\n",
    "\n",
    "Because $m_w$ is so large, the influence of the velocity (second term) is very low:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "6671281.9039630415 17105.833929951634\n",
      "0.25640999999999997 %\n"
     ]
    }
   ],
   "source": [
    "f_star1 = 2*m_w/c*100\n",
    "f_star2 = 2*f_0/c*33\n",
    "print(f_star1, f_star2)\n",
    "print(f_star2/f_star1*100, \"%\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "That means:\n",
    "\n",
    "\\begin{align}\n",
    "f_* \\approx \\frac{2m_w}{c}r\n",
    "\\end{align}\n",
    "\n",
    "We rearrange:\n",
    "\n",
    "\\begin{align}\n",
    "r \\approx \\frac{f_* c}{2 m_w}\n",
    "\\end{align}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "def freq_to_range(f):\n",
    "    return f*c/(2*m_w)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "ranges = freq_to_range(frequencies)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "50.215236715\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,5))\n",
    "plt.plot(ranges, 2.0/n_s*np.abs(chirp0_magnitude[0:n_s//2]))\n",
    "plt.plot(ranges, 2.0/n_s*np.abs(chirp0_magnitude[0:n_s//2]), \"k+\")\n",
    "plt.xlabel(\"range $r$ [m]\")\n",
    "plt.title(\"derived range (FFT of chirp_0)\")\n",
    "print(freq_to_range(frequencies)[np.argmax(2.0/n_s*np.abs(chirp0_magnitude[0:n_s//2]))])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Looks like we got the distance right: $\\approx 50m$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Calculate range bins for each chirp\n",
    "\n",
    "Now we do the same for each of $n_r$ chirps and save the FFT results in a table of shape $n_r × n_s/2$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "range_table = np.zeros((n_r, n_s//2), dtype=np.csingle)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "for chirp_nr in range(n_r):\n",
    "    chirp_ad_values = table_df.iloc[chirp_nr].values\n",
    "    chirp_fft = fft(chirp_ad_values) # FFT\n",
    "    range_table[chirp_nr, :] = 2.0/n_s*chirp_fft[:n_s//2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's visualize the table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x1000 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(nrows=2, ncols=2, figsize=(15,10), sharex=True, sharey=True)\n",
    "abs_axes = ax[0, 0]\n",
    "phi_axes = ax[0, 1]\n",
    "real_axes = ax[1, 0]\n",
    "imag_axes = ax[1, 1]\n",
    "\n",
    "im_asb = abs_axes.imshow(np.abs(range_table), cmap = plt.get_cmap('RdYlBu'))\n",
    "abs_axes.set_xticks(range(ranges.size)[::50])\n",
    "abs_axes.set_xticklabels(ranges[::50], rotation=90)\n",
    "fig.colorbar(im_asb, ax=abs_axes)\n",
    "abs_axes.set_xlabel(\"range [m]\")\n",
    "abs_axes.set_ylabel(\"chirp number\")\n",
    "abs_axes.set_title(\"$|A(j\\omega)|$\")\n",
    "\n",
    "im_phi = phi_axes.imshow(np.angle(range_table)*360/(2*np.pi), cmap = plt.get_cmap('RdYlBu'))\n",
    "fig.colorbar(im_phi, ax=phi_axes)\n",
    "phi_axes.set_xlabel(\"range [m]\")\n",
    "phi_axes.set_ylabel(\"chirp number\")\n",
    "phi_axes.set_title(\"$∠ A(j\\omega)$\")\n",
    "phi_axes.set_xticks(range(ranges.size)[::50])\n",
    "phi_axes.set_xticklabels(ranges[::50], rotation=90)\n",
    "\n",
    "im_real = real_axes.imshow(np.real(range_table), cmap = plt.get_cmap('RdYlBu'))\n",
    "fig.colorbar(im_real, ax=real_axes)\n",
    "real_axes.set_xlabel(\"range [m]\")\n",
    "real_axes.set_ylabel(\"chirp number\")\n",
    "real_axes.set_title(\"Real{$A(j\\omega)$}\")\n",
    "real_axes.set_xticks(range(ranges.size)[::50])\n",
    "real_axes.set_xticklabels(ranges[::50], rotation=90)\n",
    "\n",
    "im_imag = imag_axes.imshow(np.imag(range_table), cmap = plt.get_cmap('RdYlBu'))\n",
    "fig.colorbar(im_imag, ax=imag_axes)\n",
    "imag_axes.set_xlabel(\"range [m]\")\n",
    "imag_axes.set_ylabel(\"chirp number\")\n",
    "imag_axes.set_title(\"Imag{$A(j\\omega)$}\");\n",
    "imag_axes.set_xticks(range(ranges.size)[::50])\n",
    "imag_axes.set_xticklabels(ranges[::50], rotation=90);\n",
    "\n",
    "fig.suptitle(\"Range FFT table visualized.\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Velocity estimation\n",
    "\n",
    "We make a second FFT over each range bin (column).\n",
    "\n",
    "Again, we initialize an empty table. Now the rows will be different velocity ranges."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "velocity_table = np.zeros((n_r, range_table.shape[1]), dtype=np.csingle)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "for r in range(range_table.shape[1]):\n",
    "    range_bin_magn = range_table[:, r]\n",
    "    range_bin_fft = fft(range_bin_magn)\n",
    "    velocity_table[:, r]= 2.0/n_r*range_bin_fft"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Second FFT on columns returns the phase shift\n",
    "\n",
    "\\begin{align}\n",
    "... + \\frac{4 \\pi f_0 }{c} r = ... + \\frac{4 \\pi f_0 }{c} vt \\\\\n",
    "\\Rightarrow \\frac{4 \\pi f_0 }{c}v = \\omega_{\\text{FFT, columns}}\n",
    "\\end{align}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After rearranging ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "def angle_freq_to_velocity(w):\n",
    "    return w*c/(4*np.pi*f_0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "omega_second = 2*np.pi*np.concatenate((np.arange(0, n_r//2), np.arange(-n_r//2, 0)[::-1]))*f_chirp/n_r"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "velocities = angle_freq_to_velocity(omega_second)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,10))\n",
    "plt.imshow(np.abs(velocity_table), cmap = plt.get_cmap('RdYlBu'))\n",
    "plt.xticks(range(ranges.size)[::20], ranges[::20], rotation=90);\n",
    "plt.yticks(range(velocities.size)[::10], velocities[::10]);\n",
    "plt.xlim([0, 200])\n",
    "plt.xlabel(\"range $r$ [m]\")\n",
    "plt.ylabel(\"velocity $\\\\dot r = v$ [m/s]\");\n",
    "plt.title(\"Chirp Sequence Modulation Result - $r, \\\\dot r$ map\")\n",
    "plt.colorbar();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you can see, we could successfully recognize (blue dot) the target in 50m range with velocity of $10 m/s$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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