transmit_along_path: Simulate telemetry transmitter signals along a path

In ocean-tracking-network/glatos: A package for the Great Lakes Acoustic Telemetry Observation System

Simulate telemetry transmitter signals along a path

Description

Simulate tag signal transmission along a pre-defined path (x, y coords) based on constant movement velocity, transmitter delay range, and duration of signal.

Usage

transmit_along_path(
  path = NA,
  vel = 0.5,
  delayRng = c(60, 180),
  burstDur = 5,
  colNames = list(x = "x", y = "y"),
  pathCRS = NA,
  sp_out = TRUE
)

Arguments

path	A data frame or matrix with at least two rows and named columns with coordinates that define path. OR A object of class sf::sf() or sf::sfc() containing POINT features with a geometry column. (sp::SpatialPointsDataFrame() is also allowed.)
vel	A numeric scalar with movement velocity along track; assumed constant; in meters per second.
delayRng	A 2-element numeric vector with minimum and maximum delay (time in seconds from end of one coded burst to beginning of next).
burstDur	A numeric scalar with duration (in seconds) of each coded burst (i.e., pulse train).
colNames	A named list containing the names of columns with coordinates (defaults are x and y) in path. Ignored if trnsLoc is a spatial object with a geometry column.
pathCRS	Defines the coordinate reference system (object of class crs or a numeric EPSG code) of coordinates in path, if missing; ignored otherwise. If no valid crs is specified in path or via pathCRS = NA (default value), then path coordinates are assumed to be in an arbitrary Cartesian coordinate system with base unit of 1 meter. See Note.
sp_out	Logical. If TRUE (default) then output is an sf object. If FALSE, then output is a data.frame.

Details

Delays are drawn from uniform distribution defined by delay range. First, elapsed time in seconds at each vertex in path is calculated based on path length and velocity. Next, delays are simulated and burst durations are added to each delay to determine the time of each signal transmission. Location of each signal transmission along the path is linearly interpolated.

Computation time is fastest if coordinates in path are in a Cartesian (projected) coordinate system and slowest if coordinates are in a geographic coordinate system (e.g., longitude, latitude) because different methods are used to calculate step lengths in each case. When path CRS is Cartesian (e.g., UTM), step lengths are calculated as simple Euclidean distance. When CRS is geographic, step lengths are calculated as Haversine distances using geodist::geodist() (with measure = "haversine").

Value

When sp_out = TRUE, an sf object containing one POINT feature for each simulated transmission and a column named time (defined below).

When sp_out = FALSE, a data.frame with the following columns:

x	x coordinates for start of each transmission.
y	y coordinates for start of each transmission.
time	Elapsed time, in seconds, from the start of input path to the start of each transmission.

Note

This function was written to be called after crw_in_polygon() and before detect_transmissions(), which was designed to accept the result as input (trnsLoc).

Author(s)

C. Holbrook [e-mail]

Examples

# Example 1 - data.frame input (default column names)

mypath <- data.frame(
  x = seq(0, 1000, 100),
  y = seq(0, 1000, 100)
)

mytrns <- transmit_along_path(mypath,
  vel = 0.5,
  delayRng = c(60, 180),
  burstDur = 5.0,
  sp_out = FALSE
)
plot(mypath, type = "o")
points(mytrns, pch = 20, col = "red")


# Example 2 - data.frame input (non-default column names)

mypath <- data.frame(
  Easting = seq(0, 1000, 100),
  Northing = seq(0, 1000, 100)
)

mytrns <- transmit_along_path(mypath,
  vel = 0.5, delayRng = c(60, 180),
  burstDur = 5.0,
  colNames = list(
    x = "Easting",
    y = "Northing"
  ),
  sp_out = FALSE
)
plot(mypath, type = "o")
points(mytrns, pch = 20, col = "red")


# Example 3 - data.frame input using pathCRS arg

mypath <- data.frame(
  deploy_long = c(-87, -87.1, -87),
  deploy_lat = c(44, 44.1, 44.2)
)

mytrns <- transmit_along_path(mypath,
  vel = 0.5, delayRng = c(600, 1800),
  burstDur = 5.0,
  colNames = list(
    x = "deploy_long",
    y = "deploy_lat"
  ),
  pathCRS = 4326,
  sp_out = FALSE
)
plot(mypath, type = "o")
points(mytrns, pch = 20, col = "red")


# Example 4 - sf POINT input

# simulate in great lakes polygon
data(great_lakes_polygon)

mypath_sf <- crw_in_polygon(great_lakes_polygon,
  theta = c(0, 25),
  stepLen = 100,
  initHeading = 0,
  nsteps = 10,
  cartesianCRS = 3175
)

mytrns_sf <- transmit_along_path(mypath_sf,
  vel = 0.5,
  delayRng = c(60, 180),
  burstDur = 5.0
)
plot(mypath_sf, type = "o")
points(sf::st_coordinates(mytrns_sf), pch = 20, col = "red")


# Example 5 - SpatialPointsDataFrame input

# simulate in great lakes polygon
data(greatLakesPoly)

mypath_sp <- crw_in_polygon(greatLakesPoly,
  theta = c(0, 25),
  stepLen = 100,
  initHeading = 0,
  nsteps = 10,
  cartesianCRS = 3175
)

mytrns_sp <- transmit_along_path(mypath_sp,
  vel = 0.5,
  delayRng = c(60, 180),
  burstDur = 5.0
)

plot(sf::st_coordinates(sf::st_as_sf(mypath_sp)), type = "o")
points(sf::st_coordinates(mytrns_sp), pch = 20, col = "red")

ocean-tracking-network/glatos documentation built on April 17, 2025, 10:38 p.m.