Haskell, S.P., and W.B. Ballard (in review) Accounting for radiotelemetry signal flux in triangulation point estimation.  European Journal of Wildlife Research 00:000–000.  

other keywords: MATLAB, maximum likelihood, Texas Tech University , weighted-incenter, wildlife

Output generated by the given command in MATLAB with input variables previously defined.  A plot generated by triangulation.m from initial Haskell&Ballard beacon study  observations showing 2 separate triangulations from 6 different telemetry stations on 1 radio-beacon (+).  Estimated locations signified by red "x".  Selected output data show estimated UTM coordinates, whether or not all rays in a triangulation observation cross, method used for location estimation, number of iterations to satisfy the optimization algorithm, predicted linear error by site-specific regression formula, actual linear error from location estimates to known beacon location, and signed angle errors.  See link to download m.files and original Haskell&Ballard beacon study dataset.  

zip file containing my triangulation and associated MATLAB functions along with our dataset from the ms in Excel and some documentation in Word

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[locest,cross,method,endloop,PredLinErr,trilinerr,anglerrs] = triangulation(telsta1,az1,sig1,telsta2,az2,sig2,telsta3,az3,sig3,transloc)

count =     1

count =     2

locest =          241687.166712629          3426856.48038987

                        241765.327674077           3426634.4441303

cross =     1

                  1

method =     0

                      1

endloop =    15

                      5

PredLinErr =           70.788034477364

                                  128.196467124775

trilinerr =          92.0435971467921

                           157.628084814361

anglerrs =         -2.21501284259659         -3.44872838264894          1.17519659261666

                            1.31714317083659         -7.25528486948826         -1.49165600274188