calc_collision_prob: Estimate probability of collision for telemetry transmitters

In jsta/glatos: A package for the Great Lakes Acoustic Telemetry Observation System

Estimate probability of collision for telemetry transmitters

Description

Estimate (by simulation) probability of collision for co-located telemetry transmitters with pulse-period-modulation type encoding

Usage

calc_collision_prob(delayRng = c(60, 180), burstDur = 5,
  maxTags = 50, nTrans = 10000)

Arguments

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).
maxTags	A numeric scalar with maximum number of co-located transmitters (within detection range at same time).
nTrans	A numeric scalar with the number of transmissions to simulate for each co-located transmitter.

Details

Calculates the detection probability associated with collision, given delay range (delayRng), burst duration (burstDur), maximum number of co-located tags (maxTags), and number of simulated transmission per tag (nTrans). The simulation estimates detection probability due only to collisions (i.e., when no other variables influence detection probability) and assuming that all tags are co-located at a receiver for the duration of the simulation.

Value

A data frame containing summary statistics:

nTags	Number of tags within detection range at one time
min	Minimum detection probability among simulated tags
q1	First quartile of detection probabilities among simulated tags
median	Median detection probability among simulated tags
q3	Third quartile of detection probabilities among simulated tags
max	Maximum detection probability among simulated tags
mean	Mean detection probability among simulated tags
expDetsPerHr	Expected number of detections per hour assuming perfect detection probability, given the number of tags within detection range
totDetsPerHr	Observed number of detections per hour for a given number of tags
effDelay	Eeffective delay of the transmitter after incorporating collisions
detsPerTagPerHr	Mean number of detections per hour per tag

Author(s)

C. Holbrook ([e-mail]) and T. Binder

References

For application example, see:

Binder, T.R., Holbrook, C.M., Hayden, T.A. and Krueger, C.C., 2016. Spatial and temporal variation in positioning probability of acoustic telemetry arrays: fine-scale variability and complex interactions. Animal Biotelemetry, 4(1):1.
http://animalbiotelemetry.biomedcentral.com/articles/10.1186/s40317-016-0097-4

Examples

#parameters analagous to Vemco tag, global coding, 45 s nominal delay
foo <- calc_collision_prob(delayRng = c(45, 90), burstDur = 5.12, maxTags = 50,
    nTrans = 10000)
    
#plot probabilities of detection
plot(med~nTags, data=foo, type='p', pch=20, ylim=c(0,1),
  b
  
#plot probability of collision by subtracting detection probability from 1
plot((1 - med)~nTags, data=foo, type='p', pch=20, ylim=c(0,1),
  xlab="# of transmitters within range", ylab="Probability of collision")

jsta/glatos documentation built on July 11, 2022, 7:01 a.m.