From 87d32c566e7c8d78fb5145b35f37ce4c9894e080 Mon Sep 17 00:00:00 2001
From: Jesse Mapel <jmapel@usgs.gov>
Date: Thu, 30 Apr 2020 10:28:21 -0700
Subject: [PATCH] Added ISD generation notebooks (#282)
* Added notebooks
* Updated SAR notebook
---
.../Generate_Nadir_pointing.ipynb | 148 ++++++++++
jupyter_notebooks/OrbitalLsGeneration.ipynb | 137 +++++++++
jupyter_notebooks/OrbitalSarGeneration.ipynb | 259 ++++++++++++++++++
3 files changed, 544 insertions(+)
create mode 100644 jupyter_notebooks/Generate_Nadir_pointing.ipynb
create mode 100644 jupyter_notebooks/OrbitalLsGeneration.ipynb
create mode 100644 jupyter_notebooks/OrbitalSarGeneration.ipynb
diff --git a/jupyter_notebooks/Generate_Nadir_pointing.ipynb b/jupyter_notebooks/Generate_Nadir_pointing.ipynb
new file mode 100644
index 0000000..3885879
--- /dev/null
+++ b/jupyter_notebooks/Generate_Nadir_pointing.ipynb
@@ -0,0 +1,148 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "ModuleNotFoundError",
+ "evalue": "No module named 'pyproj'",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)",
+ "\u001b[0;32m<ipython-input-1-7e71c9f92a96>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mnumpy\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_printoptions\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msuppress\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0mpyproj\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+ "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'pyproj'"
+ ]
+ }
+ ],
+ "source": [
+ "import numpy as np\n",
+ "np.set_printoptions(suppress=True)\n",
+ "import pyproj"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def reproject(record, semi_major, semi_minor, source_proj, dest_proj, **kwargs):\n",
+ " \"\"\"\n",
+ " Thin wrapper around PyProj's Transform() function to transform 1 or more three-dimensional\n",
+ " point from one coordinate system to another. If converting between Cartesian\n",
+ " body-centered body-fixed (BCBF) coordinates and Longitude/Latitude/Altitude coordinates,\n",
+ " the values input for semi-major and semi-minor axes determine whether latitudes are\n",
+ " planetographic or planetocentric and determine the shape of the datum for altitudes.\n",
+ " If semi_major == semi_minor, then latitudes are interpreted/created as planetocentric\n",
+ " and altitudes are interpreted/created as referenced to a spherical datum.\n",
+ " If semi_major != semi_minor, then latitudes are interpreted/created as planetographic\n",
+ " and altitudes are interpreted/created as referenced to an ellipsoidal datum.\n",
+ " Parameters\n",
+ " ----------\n",
+ " record : object\n",
+ " Pandas series object\n",
+ " semi_major : float\n",
+ " Radius from the center of the body to the equater\n",
+ " semi_minor : float\n",
+ " Radius from the pole to the center of mass\n",
+ " source_proj : str\n",
+ " Pyproj string that defines a projection space ie. 'geocent'\n",
+ " dest_proj : str\n",
+ " Pyproj string that defines a project space ie. 'latlon'\n",
+ " Returns\n",
+ " -------\n",
+ " : list\n",
+ " Transformed coordinates as y, x, z\n",
+ " \"\"\"\n",
+ " source_pyproj = pyproj.Proj(proj = source_proj, a = semi_major, b = semi_minor)\n",
+ " dest_pyproj = pyproj.Proj(proj = dest_proj, a = semi_major, b = semi_minor)\n",
+ "\n",
+ " y, x, z = pyproj.transform(source_pyproj, dest_pyproj, record[0], record[1], record[2], **kwargs)\n",
+ "\n",
+ " return y, x, z"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Input Data"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "semi_major = 1100\n",
+ "semi_minor = 1000\n",
+ "altitude = 50\n",
+ "lon = 35\n",
+ "lat = 30\n",
+ "radius = 0"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Compute the quaternion (as x, y, z, w)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[ 0.49673176 -0.70940648 0. -0.5 ]\n"
+ ]
+ }
+ ],
+ "source": [
+ "ground_pt = np.asarray(reproject([lon, lat, radius], semi_major, semi_minor, 'latlong', 'geocent'))\n",
+ "sensor_position = np.asarray(reproject([lon, lat, radius + altitude], semi_major, semi_minor, 'latlong', 'geocent'))\n",
+ "look_vec = ground_pt - sensor_position\n",
+ "look_vec = look_vec / np.linalg.norm(look_vec)\n",
+ "quat = np.zeros(4)\n",
+ "quat[:3] = np.cross(np.array([0, 0, 1]), look_vec)\n",
+ "quat[3] = np.dot(np.array([0, 0, 1]), look_vec)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "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": "3.7.1"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/jupyter_notebooks/OrbitalLsGeneration.ipynb b/jupyter_notebooks/OrbitalLsGeneration.ipynb
new file mode 100644
index 0000000..8e4f02c
--- /dev/null
+++ b/jupyter_notebooks/OrbitalLsGeneration.ipynb
@@ -0,0 +1,137 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import numpy as np\n",
+ "np.set_printoptions(suppress=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "radius = 10 # km\n",
+ "altitude = 9990 # km\n",
+ "detector_size = 0.1 # mm\n",
+ "focal_length = 50 # mm\n",
+ "lines = 16\n",
+ "exposure_duration = 0.1 # seconds"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[1050. 0. -0.]\n",
+ "[1049.99999524 0. -0.1 ]\n",
+ "[1049.99998095 0. -0.2 ]\n",
+ "[1049.99995714 0. -0.3 ]\n",
+ "[1049.99992381 0. -0.39999999]\n",
+ "[1049.99988095 0. -0.49999998]\n",
+ "[1049.99982857 0. -0.59999997]\n",
+ "[1049.99976667 0. -0.69999995]\n",
+ "[1049.99969524 0. -0.79999992]\n",
+ "[1049.99961429 0. -0.89999989]\n",
+ "[1049.99952381 0. -0.99999985]\n",
+ "[1049.99942381 0. -1.0999998 ]\n",
+ "[1049.99931429 0. -1.19999974]\n",
+ "[1049.99919524 0. -1.29999967]\n",
+ "[1049.99906667 0. -1.39999959]\n",
+ "[1049.99892857 0. -1.49999949]\n",
+ "[ -0. 0. -1050.]\n",
+ "[ -0.1 0. -1049.99999524]\n",
+ "[ -0.2 0. -1049.99998095]\n",
+ "[ -0.3 0. -1049.99995714]\n",
+ "[ -0.39999999 0. -1049.99992381]\n",
+ "[ -0.49999998 0. -1049.99988095]\n",
+ "[ -0.59999997 0. -1049.99982857]\n",
+ "[ -0.69999995 0. -1049.99976667]\n",
+ "[ -0.79999992 0. -1049.99969524]\n",
+ "[ -0.89999989 0. -1049.99961429]\n",
+ "[ -0.99999985 0. -1049.99952381]\n",
+ "[ -1.0999998 0. -1049.99942381]\n",
+ "[ -1.19999974 0. -1049.99931429]\n",
+ "[ -1.29999967 0. -1049.99919524]\n",
+ "[ -1.39999959 0. -1049.99906667]\n",
+ "[ -1.49999949 0. -1049.99892857]\n",
+ "[ 0. -0.70710678 0. 0.70710678]\n",
+ "[ 0. -0.70707311 0. 0.70714045]\n",
+ "[ 0. -0.70703943 0. 0.70717412]\n",
+ "[ 0. -0.70700576 0. 0.70720779]\n",
+ "[ 0. -0.70697208 0. 0.70724146]\n",
+ "[ 0. -0.7069384 0. 0.70727512]\n",
+ "[ 0. -0.70690472 0. 0.70730878]\n",
+ "[ 0. -0.70687104 0. 0.70734244]\n",
+ "[ 0. -0.70683736 0. 0.7073761 ]\n",
+ "[ 0. -0.70680367 0. 0.70740976]\n",
+ "[ 0. -0.70676998 0. 0.70744342]\n",
+ "[ 0. -0.70673629 0. 0.70747707]\n",
+ "[ 0. -0.7067026 0. 0.70751073]\n",
+ "[ 0. -0.70666891 0. 0.70754438]\n",
+ "[ 0. -0.70663522 0. 0.70757803]\n",
+ "[ 0. -0.70660152 0. 0.70761168]\n"
+ ]
+ }
+ ],
+ "source": [
+ "positions = []\n",
+ "velocities = []\n",
+ "quats = []\n",
+ "for i in np.arange(0,16):\n",
+ " angle = i*detector_size/(radius+altitude)\n",
+ " position = (radius+altitude) * np.array([np.cos(angle), 0, -np.sin(angle)])\n",
+ " positions.append(position)\n",
+ " velocity = (radius+altitude) * np.array([-np.sin(angle), 0, -np.cos(angle)])\n",
+ " velocities.append(velocity)\n",
+ " camera_angle = -np.pi/2 + angle\n",
+ " quat = np.array([0, np.sin(camera_angle/2), 0, np.cos(camera_angle/2)])\n",
+ " quats.append(quat)\n",
+ "for pos in positions:\n",
+ " print(pos)\n",
+ "for vel in velocities:\n",
+ " print(vel)\n",
+ "for quat in quats:\n",
+ " print(quat)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "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": "3.7.1"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/jupyter_notebooks/OrbitalSarGeneration.ipynb b/jupyter_notebooks/OrbitalSarGeneration.ipynb
new file mode 100644
index 0000000..77afe82
--- /dev/null
+++ b/jupyter_notebooks/OrbitalSarGeneration.ipynb
@@ -0,0 +1,259 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import numpy as np\n",
+ "from itertools import product"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "radius = 1737400\n",
+ "alt = 2000000\n",
+ "ground = 7.5\n",
+ "exposure = 0.005\n",
+ "samples = 1000\n",
+ "lines = 1000"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "sensor_rad = radius + alt\n",
+ "angle_per_line = ground / radius\n",
+ "angle_per_samp = angle_per_line\n",
+ "angle_per_Second = angle_per_line / exposure"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "line_vec = np.arange(0, lines+0.00000001)\n",
+ "sample_vec = np.arange(0, samples+0.00000001)\n",
+ "# From here on, matrix indexing is [line, sample, (xyz)]\n",
+ "sample_mat, line_mat = np.meshgrid(line_vec, sample_vec)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "scrolled": true
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Positions\n",
+ "[3737400.0, 0.0, -0.0]\n",
+ "[3737399.912943243, 0.0, -806.6795148600813]\n",
+ "[3737399.651772976, 0.0, -1613.3589921395437]\n",
+ "[3737399.216489211, 0.0, -2420.03839425777]\n",
+ "[3737398.607091969, 0.0, -3226.7176836341473]\n",
+ "[3737397.823581278, 0.0, -4033.396822688066]\n",
+ "[3737396.8659571735, 0.0, -4840.075773838925]\n",
+ "[3737395.734219702, 0.0, -5646.754499506133]\n",
+ "[3737394.4283689144, 0.0, -6453.432962109106]\n",
+ "[3737392.9484048723, 0.0, -7260.111124067275]\n",
+ "[3737391.2943276456, 0.0, -8066.788947800085]\n",
+ "[3737389.4661373096, 0.0, -8873.466395726995]\n",
+ "[3737387.4638339505, 0.0, -9680.14343026748]\n",
+ "[3737385.287417662, 0.0, -10486.820013841041]\n",
+ "[3737382.936888544, 0.0, -11293.496108867193]\n",
+ "[3737380.4122467074, 0.0, -12100.17167776548]\n",
+ "[3737377.713492269, 0.0, -12906.846682955462]\n",
+ "[3737374.840625355, 0.0, -13713.521086856732]\n",
+ "[3737371.7936460995, 0.0, -14520.194851888911]\n",
+ "[3737368.5725546437, 0.0, -15326.867940471646]\n",
+ "[3737365.177351138, 0.0, -16133.540315024618]\n",
+ "Velocities\n",
+ "[-0.0, 0.0, -3737400.0]\n",
+ "[-806.6795148600813, 0.0, -3737399.912943243]\n",
+ "[-1613.3589921395437, 0.0, -3737399.651772976]\n",
+ "[-2420.03839425777, 0.0, -3737399.216489211]\n",
+ "[-3226.7176836341473, 0.0, -3737398.607091969]\n",
+ "[-4033.396822688066, 0.0, -3737397.823581278]\n",
+ "[-4840.075773838925, 0.0, -3737396.8659571735]\n",
+ "[-5646.754499506133, 0.0, -3737395.734219702]\n",
+ "[-6453.432962109106, 0.0, -3737394.4283689144]\n",
+ "[-7260.111124067275, 0.0, -3737392.9484048723]\n",
+ "[-8066.788947800085, 0.0, -3737391.2943276456]\n",
+ "[-8873.466395726995, 0.0, -3737389.4661373096]\n",
+ "[-9680.14343026748, 0.0, -3737387.4638339505]\n",
+ "[-10486.820013841041, 0.0, -3737385.287417662]\n",
+ "[-11293.496108867193, 0.0, -3737382.936888544]\n",
+ "[-12100.17167776548, 0.0, -3737380.4122467074]\n",
+ "[-12906.846682955462, 0.0, -3737377.713492269]\n",
+ "[-13713.521086856732, 0.0, -3737374.840625355]\n",
+ "[-14520.194851888911, 0.0, -3737371.7936460995]\n",
+ "[-15326.867940471646, 0.0, -3737368.5725546437]\n",
+ "[-16133.540315024618, 0.0, -3737365.177351138]\n"
+ ]
+ }
+ ],
+ "source": [
+ "positions = sensor_rad * np.vstack([np.cos(-angle_per_line * line_vec), np.zeros(line_vec.shape), np.sin(-angle_per_line * line_vec)]).T\n",
+ "# Note: The chain rule results in an extra negative on the velocity calculations\n",
+ "velocities = sensor_rad * np.vstack([np.sin(-angle_per_line * line_vec), np.zeros(line_vec.shape), -np.cos(-angle_per_line * line_vec)]).T\n",
+ "print('Positions')\n",
+ "for pos in positions[::int(0.25/exposure)]:\n",
+ " print(list(pos))\n",
+ "print('Velocities')\n",
+ "for vel in velocities[::int(0.25/exposure)]:\n",
+ " print(list(vel))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "scrolled": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Ground point at line: 500, sample: 500\n",
+ "[1737391.90602155 -3749.98835331 -3749.99708833]\n"
+ ]
+ }
+ ],
+ "source": [
+ "lat = -angle_per_line * line_mat\n",
+ "# Image is a right look, so the longitude goes negative\n",
+ "lon = -angle_per_samp * sample_mat\n",
+ "ground_points = radius * np.stack([np.multiply(np.cos(lat), np.cos(lon)), np.multiply(np.cos(lat), np.sin(lon)), np.sin(lat)], axis=-1)\n",
+ "print(\"Ground point at line: 500, sample: 500\")\n",
+ "print(ground_points[500, 500])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {
+ "scrolled": true
+ },
+ "outputs": [],
+ "source": [
+ "slant_range = np.array([[np.linalg.norm(point) for point in row] for row in ground_points - positions[:, None, :]])\n",
+ "ground_range = radius * np.abs(lon)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Ground range to slant range polynomial coefficients\n",
+ "[2000000.000003915, -1.0488420462327845e-08, 5.377893056639776e-07, -1.3072058387193456e-15]\n"
+ ]
+ }
+ ],
+ "source": [
+ "range_poly = np.polynomial.polynomial.polyfit(ground_range.flatten(), slant_range.flatten(), 3)\n",
+ "print(\"Ground range to slant range polynomial coefficients\")\n",
+ "print(list(range_poly))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Locus point: [1737392.0956685692, -3849.7959147875467, -3749.9887626446034]\n",
+ "Locus direction: [0.0019248861951120758, -0.9999981473962212, -4.154676206387554e-06]\n"
+ ]
+ }
+ ],
+ "source": [
+ "sc_pos = positions[500]\n",
+ "sc_vel = velocities[500]\n",
+ "off_ground_pt = ground_points[500, 500] - np.array([100, 100, 100])\n",
+ "look_vec = off_ground_pt - positions[500]\n",
+ "zero_doppler_look_vec = look_vec - np.dot(look_vec, sc_vel) / np.dot(sc_vel, sc_vel) * sc_vel\n",
+ "locus_point = sc_pos + slant_range[500, 500] / np.linalg.norm(zero_doppler_look_vec) * zero_doppler_look_vec\n",
+ "# Image is a right look, so do look X velocity\n",
+ "locus_direction = np.cross(zero_doppler_look_vec, sc_vel)\n",
+ "locus_direction = 1.0 / np.linalg.norm(locus_direction) * locus_direction\n",
+ "print(\"Locus point:\", list(locus_point))\n",
+ "print(\"Locus direction:\", list(locus_direction))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Remote locus point: [1737388.3904556318, 0.0, -3749.980765309453]\n",
+ "Remote locus direction: [-0.0, -1.0, 0.0]\n"
+ ]
+ }
+ ],
+ "source": [
+ "remote_look_vec = -slant_range[500, 500] / sensor_rad * sc_pos\n",
+ "remote_zero_doppler_look_vec = remote_look_vec - np.dot(remote_look_vec, sc_vel) / np.dot(sc_vel, sc_vel) * sc_vel\n",
+ "remote_locus_point = sc_pos + remote_zero_doppler_look_vec\n",
+ "remote_locus_direction = np.cross(remote_zero_doppler_look_vec, sc_vel)\n",
+ "remote_locus_direction = 1.0 / np.linalg.norm(remote_locus_direction) * remote_locus_direction\n",
+ "print(\"Remote locus point:\", list(remote_locus_point))\n",
+ "print(\"Remote locus direction:\", list(remote_locus_direction))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "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": "3.7.1"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
--
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