{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Tutorial 07: Initial Orbit Determination and Lambert's Problem\n", "\n", "This tutorial demonstrates how to determine a spacecraft's orbit from observations and how to solve for trajectories between two points in space.\n", "\n", "## 1. Initial Orbit Determination (IOD)\n", "IOD is the process of estimating an initial state vector (position and velocity) from a set of observations, usually angles-only (Line-of-Sight) or range-and-angles.\n", "\n", "### Gauss's Method\n", "Gauss's method uses **three line-of-sight (LOS) vectors** from a single observation site to determine the orbit. It solves eighth-order polynomial for the radius of the middle observation and then uses universal variables to refine the estimate iterative.\n", "\n", "## Theory Prerequisites\n", "\n", "Given three unit vectors $\\hat{\\rho}_1, \\hat{\\rho}_2, \\hat{\\rho}_3$ and observer positions $R_1, R_2, R_3$, the satellite position is:\n", "$$\n", "r_i = R_i + \\rho_i \\hat{\\rho}_i\n", "$$\n", "Gauss solves for the scalar ranges $\\rho_i$ by enforcing the coplanarity condition and Keplerian dynamics.\n", "\n", "---" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Imports successful.\n" ] } ], "source": [ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "from opengnc.navigation.iod import gauss_iod\n", "from opengnc.guidance.rendezvous import solve_lambert\n", "from opengnc.utils.state_to_elements import kepler2eci\n", "\n", "# Helpers for generating synthetic data\n", "def solve_kepler(M, e):\n", " E = M\n", " for _ in range(10):\n", " f = E - e * np.sin(E) - M\n", " df = 1.0 - e * np.cos(E)\n", " E = E - f / df\n", " if abs(f) < 1e-12:\n", " break\n", " return E\n", "\n", "def eccentric_to_true(E, e):\n", " return 2 * np.arctan(np.sqrt((1 + e)/(1 - e)) * np.tan(E / 2.0))\n", "\n", "print(\"Imports successful.\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 1.1 Simulating Observations\n", "We will generate synthetic line-of-sight data from a ground station observing a satellite in an elliptical orbit." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "True Position at t2:\n", "[ 7229038.65030162 5016957.07127293 -4338519.24238726] m\n", "True Velocity at t2:\n", "[-4078.30278898 4314.77193985 -2479.45660733] m/s\n" ] } ], "source": [ "# Target Orbit Parameters\n", "a = 10000e3 # Semi-major axis [m]\n", "ecc = 0.05 # Eccentricity\n", "incl = np.radians(35.0)\n", "raan = np.radians(10.0)\n", "argp = np.radians(20.0)\n", "\n", "mu = 398600.4415e9 # m^3/s^2\n", "n = np.sqrt(mu / a**3)\n", "\n", "# Observation Times\n", "t2 = 1800.0\n", "dt = 300.0\n", "times = [t2 - dt, t2, t2 + dt]\n", "\n", "# Observer Position (Ground Station)\n", "R_earth = 6378137.0\n", "lat = np.radians(30.0)\n", "# Simple fixed observer in ECI for demonstration\n", "R_obs = np.array([R_earth * np.cos(lat), 0, R_earth * np.sin(lat)])\n", "\n", "rho_hats = []\n", "Rs = []\n", "true_states = []\n", "\n", "for t in times:\n", " E = solve_kepler(n * t, ecc)\n", " nu = eccentric_to_true(E, ecc)\n", " r, v = kepler2eci(a, ecc, incl, raan, argp, nu)\n", " true_states.append(np.concatenate([r, v]))\n", " \n", " rho_vec = r - R_obs\n", " rho_hats.append(rho_vec / np.linalg.norm(rho_vec))\n", " Rs.append(R_obs)\n", "\n", "true_state_t2 = true_states[1]\n", "print(f\"True Position at t2:\\n{true_state_t2[0:3]} m\")\n", "print(f\"True Velocity at t2:\\n{true_state_t2[3:6]} m/s\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 1.2 Running Gauss IOD\n", "We pass the line-of-sight vectors and timestamps to the solver." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "--- IOD Results ---\n", "Estimated Position:\n", "[ 7229038.65030161 5016957.07127288 -4338519.2423872 ] m\n", "Estimated Velocity:\n", "[-4078.08509341 4314.70835693 -2479.43923202] m/s\n", "\n", "Position Error: 0.00 m\n", "Velocity Error: 0.2275 m/s\n" ] } ], "source": [ "est_state = gauss_iod(\n", " rho_hats[0], rho_hats[1], rho_hats[2], \n", " times[0], times[1], times[2], \n", " Rs[0], Rs[1], Rs[2], mu\n", ")\n", "\n", "print(\"--- IOD Results ---\")\n", "print(f\"Estimated Position:\\n{est_state[0:3]} m\")\n", "print(f\"Estimated Velocity:\\n{est_state[3:6]} m/s\")\n", "\n", "pos_error = np.linalg.norm(est_state[0:3] - true_state_t2[0:3])\n", "vel_error = np.linalg.norm(est_state[3:6] - true_state_t2[3:6])\n", "\n", "print(f\"\\nPosition Error: {pos_error:.2f} m\")\n", "print(f\"Velocity Error: {vel_error:.4f} m/s\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "---\n", "\n", "## 2. Lambert's Problem\n", "Lambert's problem is the boundary value problem formulation of orbital mechanics: \n", "Given two position vectors $r_1, r_2$ and a transfer time $\\Delta t$, find the velocities $v_1, v_2$ at both positions.\n", "\n", "### Application: Rendezvous\n", "It is the workhorse for calculating intercept trajectories and maneuver $\\Delta V$.\n", "\n", "### 2.1 Solving Lambert Transfer\n", "We will compute a transfer from position A to position B in a specified time." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "--- Lambert Solver Results ---\n", "Required Velocity at r1: [-3.07789022 4.87135114 -2.98489675] km/s\n", "Required Velocity at r2: [-4.89970477 3.61190438 -1.89490628] km/s\n", "\n", "True Velocity at r1: [-3.07789023 4.87135115 -2.98489675] km/s\n", "Velocity Match Error: 0.000000 km/s\n" ] } ], "source": [ "# Let's use position vectors from our previous orbit\n", "# Transfer from r1 (t1) to r3 (t3)\n", "r1 = true_states[0][0:3] / 1000.0 # Convert to km for solve_lambert\n", "r2 = true_states[2][0:3] / 1000.0 \n", "dt_flight = times[2] - times[0] # 600 seconds\n", "\n", "mu_km = mu / 1e9 # km^3/s^2\n", "\n", "v1_req, v2_req = solve_lambert(r1, r2, dt_flight, mu=mu_km)\n", "\n", "print(\"--- Lambert Solver Results ---\")\n", "print(f\"Required Velocity at r1: {v1_req} km/s\")\n", "print(f\"Required Velocity at r2: {v2_req} km/s\")\n", "\n", "true_v1 = true_states[0][3:6] / 1000.0\n", "print(f\"\\nTrue Velocity at r1: {true_v1} km/s\")\n", "print(f\"Velocity Match Error: {np.linalg.norm(v1_req - true_v1):.6f} km/s\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 2.2 Visualization\n", "Let's plot the trajectory of the orbit." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from opengnc.propagators.kepler import KeplerPropagator\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "\n", "fig = plt.figure(figsize=(10, 8))\n", "ax = fig.add_subplot(111, projection='3d')\n", "\n", "# Propagate Trajectory Arc\n", "prop = KeplerPropagator(mu=mu_km)\n", "num_points = 100\n", "t_span = np.linspace(0, dt_flight, num_points)\n", "arc_positions = []\n", "\n", "for t in t_span:\n", " r_prop, _ = prop.propagate(r1, v1_req, t)\n", " arc_positions.append(r_prop)\n", "\n", "arc_positions = np.array(arc_positions)\n", "\n", "# Plot Arc\n", "ax.plot(arc_positions[:, 0], arc_positions[:, 1], arc_positions[:, 2], 'g-', linewidth=2, label=\"Lambert Transfer Arc\")\n", "\n", "# Plot Endpoints\n", "ax.plot([r1[0], r2[0]], [r1[1], r2[1]], [r1[2], r2[2]], 'ro', label=\"Endpoints\")\n", "\n", "# Quiver for velocity vector at r1\n", "ax.quiver(r1[0], r1[1], r1[2], v1_req[0], v1_req[1], v1_req[2], length=100, color='b', label=\"V1 Req\")\n", "\n", "# Draw simple sphere for Earth\n", "u = np.linspace(0, 2 * np.pi, 100)\n", "v = np.linspace(0, np.pi, 100)\n", "x = 6378 * np.outer(np.cos(u), np.sin(v))\n", "y = 6378 * np.outer(np.sin(u), np.sin(v))\n", "z = 6378 * np.outer(np.ones(np.size(u)), np.cos(v))\n", "ax.plot_surface(x, y, z, color='cyan', alpha=0.1)\n", "\n", "# Adjust View\n", "min_x, max_x = np.min(arc_positions[:, 0]), np.max(arc_positions[:, 0])\n", "min_y, max_y = np.min(arc_positions[:, 1]), np.max(arc_positions[:, 1])\n", "min_z, max_z = np.min(arc_positions[:, 2]), np.max(arc_positions[:, 2])\n", "\n", "margin = 50.0 # km\n", "ax.set_xlim([min_x - margin, max_x + margin])\n", "ax.set_ylim([min_y - margin, max_y + margin])\n", "ax.set_zlim([min_z - margin, max_z + margin])\n", "\n", "ax.set_box_aspect([1,1,1]) # Equal aspect ratio\n", "\n", "ax.set_xlabel('X [km]')\n", "ax.set_ylabel('Y [km]')\n", "ax.set_zlabel('Z [km]')\n", "ax.set_title('Lambert Transfer Trajectory arc and endpoints')\n", "ax.legend()\n", "\n", "plt.show()" ] } ], "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": "3.10.11" } }, "nbformat": 4, "nbformat_minor": 4 }