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1 INTRODUCTION
The need for an accurate and resilient situational
awareness has been increasingly growing in the
maritimedomainduetoavarietyofreasons:theever
increasing global trade constantly calls for ships
larger in size and numbers, which still need to
navigatetheinternationalwaterwaysandharborsina
secure and efficient manner. In addition, it is a
stringentnecessitytot
rafficmanagementandsecurity
authorities to detect abnormal vessel behavior, to
prevent harm to marine infrastructure, humans and
nature. Apart from that, the trend towards
autonomous navigation is clearly entering the
maritime world calling for advanced solutions as
enabling technologies. From our perspective two
conclusionscanbedrawnfromtheseconsiderat
ions:
firstly,maritimesituationawarenessiscrucialtoallof
these applications and secondly, the described
challenges call for a refined and more reliable
situation picture. The dominating source for traffic
situationassessmentinthemaritimedomainhasbeen
and will be the ma
rine radar, which is still the
primary sensor for collision avoidance. Various
approaches have been published in the literature to
augmentmaritimesurveillanceorcollisionavoidance
systems,mostlybasedonradarfusionwithadditional
sensors such as laser in Perera, Ferrari, Santos,
Hinostroza,and Soares (2015) or mult
iple stationary
radarsystemsforexploitingaspectanglediversityas
inBraca,Vespe,Maresca,andHorstmann(2012).The
matterofAISandradarfusionwasmainlyaddressed
foranomalydetection,e.g.,basedonmultihypothesis
tests in Guerriero, Willett, Coraluppi, and Carthel
(2008) or by exploiting historical traffic route
knowledge for SAR/AIS fusion in Mazzarella and
Vespe(2015).InKazim
ierskiandStateczny(2015)an
overview was given for different AIS/radar fusion
techniques incorporating online covariance
estimation. In Siegert, Banyś, and Heymann (2016)
and Siegert, Banyś, Hoth, and Heymann (2017),
implementations of IMMMSPDA and IMMJPDA
Validation of Radar Image Tracking Algorithms with
Simulated Data
F.Heymann,J.Hoth,P.Banyś&G.Siegert
GermanAerospaceCenter(DLR),Neustrelitz,Germany
ABSTRACT:Collisionavoidanceisoneofthehighlevelsafetyobjectivesandrequiresacompleteandreliable
description of the maritime traffic situation. The radar is specified by the IMO as the primary sensor for
collisionavoidance.Inthispaperwestudytheperformanceofmultita
rgettrackingbasedonradarimageryto
refinethemaritimetrafficsituationawareness.Inordertoachievethiswesimulatesyntheticradarimagesand
evaluatethetrackingperformanceofdifferentBayesianmultitargettrackers(MTTs),suchasparticleandJPDA
filters.Forthesimulatedtracks,thetargetstateestimatesinposition,speedandcourse overgroundwill be
compared to the reference data. The performa
nce of the MTTs will be assessed via the OSPA metric by
comparing the estimated multiobject state vector to the reference. Thisapproach allows a fair performance
analysisofdifferenttrackingalgorithmsbasedonradarimagesforasimulatedma
ritimescenario.
http://www.transnav.eu
the International Journal
on Marine Navigation
and Safety of Sea Transportation
Volume 11
Number 3
September 2017
DOI:10.12716/1001.11.03.18