Nothing
## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## ----setup--------------------------------------------------------------------
library(geographiclib)
## ----locations----------------------------------------------------------------
# Locations at various latitudes
world_pts <- cbind(
lon = c(151.21, 0, -74.01, 0, 0),
lat = c(-33.87, 51.51, 40.71, 0, -90)
)
rownames(world_pts) <- c("Sydney", "London", "New York", "Equator/Prime", "South Pole")
# Antarctic stations
antarctic <- cbind(
lon = c(166.67, 77.85, -68.13, 39.58, 0),
lat = c(-77.85, -67.60, -67.57, -69.41, -90)
)
rownames(antarctic) <- c("McMurdo", "Davis", "Palmer", "Progress", "South Pole")
## ----geocentric-basic---------------------------------------------------------
geocentric_fwd(world_pts)
## ----geocentric-structure-----------------------------------------------------
# Points on the equator have Z ≈ 0
equator_pts <- cbind(
lon = c(0, 90, 180, -90),
lat = c(0, 0, 0, 0)
)
geocentric_fwd(equator_pts)
# Points at poles have X ≈ 0, Y ≈ 0
pole_pts <- cbind(lon = c(0, 0), lat = c(90, -90))
geocentric_fwd(pole_pts)
## ----geocentric-height--------------------------------------------------------
# Ground level vs airplane altitude (10km) vs satellite (400km)
pt <- c(151.21, -33.87)
data.frame(
location = c("Ground", "Aircraft (10km)", "ISS (~400km)", "GPS satellite (~20200km)"),
h = c(0, 10000, 400000, 20200000),
geocentric_fwd(cbind(rep(pt[1], 4), rep(pt[2], 4)),
h = c(0, 10000, 400000, 20200000))
)
## ----geocentric-antarctic-----------------------------------------------------
# Antarctic stations are all near the "bottom" of the coordinate system
geocentric_fwd(antarctic)
# Note the large negative Z values (Southern Hemisphere)
# and relatively small X, Y values (near the axis)
## ----geocentric-roundtrip-----------------------------------------------------
fwd <- geocentric_fwd(world_pts)
rev <- geocentric_rev(fwd$X, fwd$Y, fwd$Z)
# Verify accuracy
max(abs(rev$lon - world_pts[,1]))
max(abs(rev$lat - world_pts[,2]))
max(abs(rev$h)) # Height should be ~0
## ----geocentric-gps-----------------------------------------------------------
# Convert GPS receiver position to geodetic
# (Example: receiver at Sydney at ~100m altitude)
X <- 4648241 # meters
Y <- -2560342
Z <- -3526276
geocentric_rev(X, Y, Z)
## ----local-basic--------------------------------------------------------------
# Set up local system centered on Sydney
sydney <- c(151.21, -33.87)
nearby_pts <- cbind(
lon = c(151.21, 151.31, 151.11, 151.21, 151.21),
lat = c(-33.87, -33.87, -33.87, -33.77, -33.97)
)
rownames(nearby_pts) <- c("Origin", "East 10km", "West 10km", "North 10km", "South 10km")
localcartesian_fwd(nearby_pts, lon0 = sydney[1], lat0 = sydney[2])
## ----local-survey-------------------------------------------------------------
# Survey points around McMurdo Station
mcmurdo <- c(166.67, -77.85)
survey_pts <- cbind(
lon = c(166.67, 166.70, 166.64, 166.67, 166.73),
lat = c(-77.85, -77.85, -77.85, -77.84, -77.86)
)
rownames(survey_pts) <- c("Base", "Point A", "Point B", "Point C", "Point D")
result <- localcartesian_fwd(survey_pts, lon0 = mcmurdo[1], lat0 = mcmurdo[2])
result
# Distances from base in meters
data.frame(
point = rownames(survey_pts),
east_m = round(result$x),
north_m = round(result$y),
distance_m = round(sqrt(result$x^2 + result$y^2))
)
## ----local-height-------------------------------------------------------------
# Local system with height differences
# Simulating a hill near Sydney
pts_with_height <- cbind(
lon = c(151.21, 151.22, 151.20),
lat = c(-33.87, -33.87, -33.86)
)
heights <- c(0, 50, 100) # meters above ellipsoid
result <- localcartesian_fwd(pts_with_height,
lon0 = 151.21, lat0 = -33.87, h0 = 0,
h = heights)
result
## ----local-roundtrip----------------------------------------------------------
pts <- cbind(
lon = c(166.67, 166.70, 166.64),
lat = c(-77.85, -77.84, -77.86)
)
fwd <- localcartesian_fwd(pts, lon0 = 166.67, lat0 = -77.85)
rev <- localcartesian_rev(fwd$x, fwd$y, fwd$z, lon0 = 166.67, lat0 = -77.85)
max(abs(rev$lon - pts[,1]))
max(abs(rev$lat - pts[,2]))
## ----local-robotics-----------------------------------------------------------
# Robot path planning at Davis Station
davis <- c(77.85, -67.60)
# Waypoints for a robot traverse
waypoints_enu <- data.frame(
name = c("Start", "WP1", "WP2", "WP3", "End"),
x = c(0, 100, 200, 250, 300), # East (meters)
y = c(0, 50, 100, 100, 150), # North (meters)
z = c(0, 0, 0, 0, 0) # Up (meters)
)
# Convert to geographic coordinates for GPS navigation
result <- localcartesian_rev(
waypoints_enu$x, waypoints_enu$y, waypoints_enu$z,
lon0 = davis[1], lat0 = davis[2]
)
data.frame(
waypoint = waypoints_enu$name,
lon = round(result$lon, 6),
lat = round(result$lat, 6)
)
## ----ellipsoid-params---------------------------------------------------------
ellipsoid_params()
## ----ellipsoid-shape----------------------------------------------------------
params <- ellipsoid_params()
# Equatorial vs polar radius difference
equatorial_radius <- params$a
polar_radius <- params$b
cat("Equatorial radius:", equatorial_radius, "m\n")
cat("Polar radius:", polar_radius, "m\n")
cat("Difference:", equatorial_radius - polar_radius, "m\n")
cat("Flattening:", 1/params$f, "(1/f)\n")
## ----ellipsoid-curvature------------------------------------------------------
# Curvature at various latitudes
lats <- c(0, -33.87, -42.88, -67.60, -77.85, -90)
names_lat <- c("Equator", "Sydney", "Hobart", "Davis", "McMurdo", "South Pole")
result <- ellipsoid_curvature(lats)
data.frame(
location = names_lat,
latitude = lats,
meridional_km = round(result$meridional / 1000, 2),
transverse_km = round(result$transverse / 1000, 2)
)
## ----ellipsoid-circle---------------------------------------------------------
# Properties of circles at different latitudes
lats <- c(0, -30, -45, -60, -75, -90)
result <- ellipsoid_circle(lats)
data.frame(
latitude = lats,
circle_radius_km = round(result$radius / 1000, 2),
meridian_dist_km = round(result$meridian_distance / 1000, 2)
)
## ----ellipsoid-auxiliary------------------------------------------------------
# Compare different latitude types at 45°S
lats <- c(0, -30, -45, -60, -90)
result <- ellipsoid_latitudes(lats)
result
# The differences are small but matter for precise calculations
## ----combined-gnss------------------------------------------------------------
# Typical GNSS workflow:
# 1. Receive ECEF coordinates from GPS
# 2. Convert to geodetic (lat/lon/height)
# 3. Convert to local for navigation
# Example GPS receiver data (ECEF, meters)
gps_ecef <- data.frame(
time = 1:5,
X = c(4648241, 4648242, 4648240, 4648243, 4648241),
Y = c(-2560342, -2560340, -2560343, -2560341, -2560342),
Z = c(-3526276, -3526275, -3526277, -3526274, -3526276)
)
# Convert to geodetic
geodetic <- geocentric_rev(gps_ecef$X, gps_ecef$Y, gps_ecef$Z)
# Convert to local (relative to first point)
local <- localcartesian_fwd(
cbind(geodetic$lon, geodetic$lat),
lon0 = geodetic$lon[1], lat0 = geodetic$lat[1], h0 = geodetic$h[1],
h = geodetic$h
)
data.frame(
time = gps_ecef$time,
east_m = round(local$x, 2),
north_m = round(local$y, 2),
up_m = round(local$z, 2)
)
## ----combined-antarctic-------------------------------------------------------
# Simulated survey data at McMurdo
mcmurdo <- c(166.67, -77.85, 10) # lon, lat, height
# Survey points in local coordinates
survey_local <- data.frame(
point = c("Control", "P1", "P2", "P3", "P4"),
east = c(0, 500, -300, 200, -100),
north = c(0, 200, 400, -150, -300),
up = c(0, 5, -2, 8, -5)
)
# Convert to geodetic for GPS upload
geodetic <- localcartesian_rev(
survey_local$east, survey_local$north, survey_local$up,
lon0 = mcmurdo[1], lat0 = mcmurdo[2], h0 = mcmurdo[3]
)
# Convert to ECEF for satellite positioning
ecef <- geocentric_fwd(
cbind(geodetic$lon, geodetic$lat),
h = geodetic$h
)
data.frame(
point = survey_local$point,
lon = round(geodetic$lon, 5),
lat = round(geodetic$lat, 5),
X = round(ecef$X),
Y = round(ecef$Y),
Z = round(ecef$Z)
)
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