429
1 INTRODUCTION
At the end of the 20th century, the dynamic
development of microelectronics caused the
popularization of unmanned aerial vehicles (UAVs),
alsocalleddrones. The UAV is an aircraft that does
not require crew on‐board and is unable to take
passengers. The UAV can be remote control by
a
human operator or autonomously by on‐board
computers.Hence,theideaoftheUAVhasitsrootsin
thesecondhalfofthelastcentury,whentheremote‐
controlled models of aircraft, cars, or ships were
mainlyofahobbynature.TheV‐1flyingbombandV‐
2
rocketfromthe2ndWorldWarcanberegardedas
theUAVprototypes.Inthepost‐warperiod,research
intothedevelopmentofthistechnologyforthearmy
needswasconductedmainlyintheUSAandUSSR.
Thisdevelopmentwasdirectlyrelatedtotheconquest
of the cosmos in which unmanned
spacecrafts, i.a.,
artificialsatellites,wereused.
Initially,duetolegalrestrictions,theUAVswere
used mainly in the armed forces [1–3]. Originally,
their main area of applications was image, optical,
and radar recognition. These are so‐called
surveillanceUAVs,e.g.,theNorthropGrummanRQ‐
4 Global Hawk. Then, the UAVs
were also used to
transposing weapons. This kind is called as a
unmanned combat aerial vehicle (UCAV), e.g., the
General Atomics MQ‐9 Reaper also called the
Errors of UAV Autonomous Landing System for
Different Radio Beacon Configurations
J
.M.Kelner&C.Ziółkowski
M
ilitaryUniversityofTechnology,Warsaw,Poland
ABSTRACT: At the turn of the 20th and 21st centuries, development of microelectronics and microwave
techniquesallowedforminimizationofelectronicdevicesandsystems,andtheuseofmicrowavefrequency
bands for modern radio communication systems. On the other hand, the global navigation satellite system
(GNSS)havecontributedtothepopularizationofradionavigationincivilianapplications.Thesefactorshada
directimpactonthedevelopmentanddisseminationofunmannedaerialvehicles(UAVs).Intheinitialperiod,
theUAVswereusedmainlyforthearmyneeds.Thisresultsalsofromthelegalaspectsofthe
UAVuseinthe
airspace. Currently, commercial UAVs for civilian applications, such as image recognition, monitoring,
transport, etc., are presented increasingly. Generally, the GNSS system accuracy for the UAV positioning
duringaflightisenough.However,theGNSSuseforautomatictakeoffandlandingmaybeinsufficient.The
extensive,ground‐based
navigationsupportsystemsusedatairportsbymannedaircrafttestifytothese.Inthe
UAVcase,suchsystemsarenotusedduetotheircomplexityandprice.Forthisreason,thenoveldedicated
take‐offandlandingsystemsaredeveloped.Theproposaloftheautonomouslandingsystem,whichisbased
ontheDopplereffect,waspresentedin2017.Inthiscase,thesquare‐basedbeaconconfigurationwasanalyzed.
ThispapershowstheinfluenceofvariousbeaconconfigurationsintheDoppler‐basedlandingsystemonthe
positioningerrorduringtheUAVlandingapproach.
http://www.transnav.eu
the International Journal
on Marine Navigation
and Safety of Sea Transportation
Volume 13
Number 2
June 2019
DOI:10.12716/1001.13.02.22
430
PredatorB.Currently,theUAVsarewidelyusedon
thecivilianmarket.Manyprivatecompaniesprovide
variousservicesusingthe UAVs,e.g.,inthe fieldof
energetics [4–7], agriculture [8,9], forestry and fire
detection [10,11], water management [12] and flood
detection [13], environmental protection [14], search
andrescue[15],radio
‐communication [16], transport
[17],etc.
The growth of the UAV market has also
contributed to the development of other unmanned
platforms,suchasunmannedground(UGVs),surface
(USVs), and underwater vehicles (UUVs). The main
recipients of this market sector are still the armed
forces of various countries. In a report
[18], the
European Commission indicates the importance of
this technology in the economic and technological
development of countries, especially in the civilian
sector[19].Accordingto the presented forecasts, the
estimated value of the UAV market in 2019 will be
expectedtoreacharound11‐12billiondollars.In2015
and
2016,thedomesticmarketwasestimatedat165
and200millionPolishzlotys,respectively[20].
Inliterature,wecanfindsynonymousfortheUAV
such as unmanned aerial system (UAS) or remotely
piloted aircraft systems (RPAS). Sometimes, the
differencesbetweentheUAVandUASareindicated.
Then, the UAV is
referred to itself aircraft platform,
while the UAS includes also other system
components,suchasthe ground‐based flight control
system. In this case, the RPAS is a synonym of the
UAS. Currently, the RPAS is more widely used in
militaryterminology,especiallyintheNorthAtlantic
Treaty Organization (NATO) and
European Defense
Agency (EDA). In the literature, various
classifications of the UAVs are presented. They
consider different technical aspects or applications.
From the viewpoint of this paper, the UAV term is
referencedtoavertical take‐off and landing (VTOL)
aircraft, unlike a conventional take‐off and landing
(CTOL)aircraft
requiringarunway.Intheremainder
ofthepaper,theVTOLisconsideredasasynonymof
theVTOLUAV.
Globalnavigationsatellitesystems(GNSSs)[21,22]
arecommonlyusedinUAVnavigation.Inaddition,
remote control and video transmission from the
aircraft to the remote UAV operator allows safe
displacement of
the drone. However, this solution
may not be sufficient to take‐off and landing
approach. This is a significant problem, notably for
theautonomousUAVs.Thetake‐offandlandingare
theaircraftflightstagesthatrequirespecialprecision
in steering and navigation. For manned aircraft, the
pilot on‐board
has more control over the plane or
helicopter.Ontheotherhand,dedicatedtake‐offand
approachsystemsareusedatlargecivilandmilitary
airports.Theinstrumentlandingsystem(ILS),tactical
air navigation system (TACAN) [23], or European
Geostationary Navigation Overlay Service (EGNOS)
[21,22]areexamplesofradiolocal‐area
augmentation
systems (LAASs). They are very important in bad
weather conditions with limited visibility, e.g., fog,
snowfall, or rain. Generally, the LAASs are not
availabletoUAVmajority.Therefore,itisimportant
todevelopsuchsolutions,especiallyforautonomous
drones.
In2016,weproposedalandingsystemonavessel
for the manned and unmanned VTOL [24]. This
system involves the use of terrestrial radio‐beacons
(RBs)andadedicatednavigationreceiver(NR)placed
onboard aircraft. In this case, the signal Doppler
frequency (SDF) location method [25–27] is used to
estimatetheaircraftpositionrelativetoalandingpad
on the
ship. This solution [24] is based on the SDF
applications dedicated to in‐flight navigation and
CTOLlandingapproach,whichareshownin[28]and
[29], respectively. Here, the analyzed concept of the
landingapproachsystemfortheunmannedVTOLis
a system modification shown in [30]. The proposed
solution
has been developed for the landing pad in
hard‐to‐reach places such as oil platforms, vessels,
islands,orskyscraperroofs.In[30],weassumedthat
RBsarelocatedbasedonasquare.Thepurposeofthis
paper is to assess the impact of selected
configurations of the RBs on the
VTOL positioning
accuracy.
The remainder of the paper is organized as
follows. Section 2 describes the SDF‐based
autonomous landing approach system. Assumptions
andsimulationscenariosarepresentedinSection3.In
Section4,theobtainedsimulationresultsareshown.
In this case, the positioning accuracy of the VTOL
UAV
fordifferentRBconfigurationsisanalyzed.The
summaryisinthefinalpartofthepaper.
2 AUTONOMOUSLANDINGAPPROACH
SYSTEMFORVTOLUAV
The spatial structure of the SDF‐based autonomous
landing approach system for the VTOL is shown in
Figure1.
Figure1.Spatialstructureofautonomouslandingapproach
systemforVTOL[30]
ThegroundpartofthesystemconsistsoffourRBs
and a measuring receiver (MR). In the solution
discussed in [30], we assumed that four RBs are
locatedbasedonthesquarearoundthelandingpad.
EachRBisequipped with a signal generator, power
amplifier, and transmitting antenna placed at
the
stand. Additionally, the RB can be equipped with a
rubidium or cesium frequency standard that will
increasethefrequencystabilityoftransmittedsignals.
ThisisimportantfromtheviewpointoftheSDFused
[31]. Three RBs, i.e., RB‐1, RB‐2, and RB‐3, transmit
harmonic signals at defined
frequencies f1, f2, and f3,
respectively. At frequency f
4, the RB‐4 transmits a
431
modulatedsignalusingdifferentialphaseshiftkeying
(DPSK).Ineachtransmittedframe,informationabout
the location coordinates of the individual RBs and
theirfrequencycorrectionsaresent.Thesecorrections
aredeterminedbasedonlocalmeasurementscarried
outbytheMRlocatednearRB‐4.
The NRs placed on the VTOLs
are the receiving
part of the system. Each VTOL is equipped with
typical elements of the navigation system, namely a
GNSS receiver and inertial navigation system (INS).
Thisallowstocarry outacontrolledorautonomous
UAV flight phase. Whereas, the NR provides
positioning the VTOL near the landing pad
and its
landingapproach.TheNRistunedtothefrequency
bandonwhichoperatetheRBs.Thismeansthatthe
NRoperationbandincludesthecarrierfrequenciesf
1,
f
2,f3,andthemodulated‐signalbandatthefrequency
f
4. The NR is made in software‐defined radio (SDR)
technology[32,33].ThismeansthattheNR provides
signal processing and determining the estimated
positionsoftheUAVrelativetothelandingpad.For
each RB, the Doppler frequency shift (DFS) is
determinedeveryspecifiedtime‐periodΔTbasedon
the
receivedsignalwiththedurationofTS.Then,the
UAV coordinates are determined based on discrete
instantaneousDFSsaggregatedinatimewindowT
A.
The method of the DFS determination for the
harmonicsignalispresentedin[25–27].Inthecaseof
the modulated signal from RB‐4, after sub‐band
filtering,informationframesaredemodulatedandthe
instantaneous DFSs are estimated based on a
methodologyshownin[34].Adetaileddescriptionof
the
autonomous landing approach system and
estimatingtheVTOLcoordinatesbasedontheSDFis
containedin[30].
The presented system can be classified as precise
short‐rangeradionavigationsystems. It can be used
duringtheUAVlandingapproach,aswellasitstake‐
off from the landing field and
in‐flight in an area,
where is a radio‐range between the NR and RBs. A
keyadvantageoftheproposedsolutionisitsnarrow
bandwithrelativelyhighpositioningprecision.Inthe
case of systems based on time measurement, e.g.,
[35,36],obtainingcomparableaccuracywouldrequire
theuseofa
muchwiderband.Wepointoutthatthe
frequencyallocationforthistypeofdedicatedsystem
is a serious problem. For the developed system,
unlicensedfrequencybands,e.g.,dedicatedtotheWi‐
Fiincludedinindustrial,scientificandmedical(ISM)
bands,canbeusedforthispurpose.Inthiscase,
the
emission of the harmonic signals with more power
than the emission average in the band does not
constituteasignificantinterferencetoothersystems.
3 SCENARIOANDASSUMPTIONSFOR
SIMULATIONSTUDIES
Inascenarioshownin[30],weassumedthattheRBs
are placed on the basis of the square
with a side
lengthequalr(seeFigure1).Inthispaper,weanalyze
three configurations of the RB positions based on
otherregularpolygons,i.e.atriangle,pentagon,and
hexagon. A common feature of all configurations is
the radius R of a circumscribed circle. Figure 2
presentstheanalyzed
RBconfigurationstogetherwith
a reference configuration based on the square (see
Figure2(b)).
Figure2. Analyzed spatial configurations of RBs based on
regular polygons: a) triangle, b) rectangle, c) pentagon, d)
hexagon
In addition, in simulation studies, we assume
similarassumptionsasin[30],i.e.,
landing point at O is the origin of the local
coordinatesystem;
the system configuration based on the regular
polygon consists of K RBs, where K
=3,4,5,6, for
the regular triangle, rectangle (i.e., square),
pentagon, and hexagon, respectively (see Figure
2);
assuming the distance r
=40m [30] between
neighboring RBs in the square configuration, the
radiusR
≈28.3misabasefordeterminingtheRB
coordinates with respect to the point O in each
configuration; the location coordinates of the
individualRBsfortheanalyzedconfigurationsare
contained in Table 1; the height of the RB
transmittingantennasish
T=zk=2mfork=1,..,K;
thesystemoperatesintheISMbandusedbythe
Wi‐Fi,i.e.,2.4GHz;ineachconfiguration,thek‐th
RB transmits the harmonic signal at f
k, where
k
=1,..,K–1; while, the K‐th RB emits the DPSK
signal at f
K; these frequencies are determined as
follows: f
K(kHz)=2399800+50∙K+100 and
f
k(kHz)=2399800+50∙(k–1) for k=1,..,K–1; the
bandwidth of the DPSK signal is equal to
B
T=80kHz;
theNRoperatesatthefrequencyf
R=2.4GHzwith
thereceptionbandB
R=500kHz;
for a Doppler curve (DFSs versus time) analysis,
thetimewindowT
A=5.0sisused;
in an electromagnetic environment, an additive
whiteGaussiannoise(AWGN)isoccurred,anda
leveloftheemittedsignalsatthefarthestpoint(L)
ofananalyzedtrajectoryisensuredbyasignal‐to‐
noiseratioequaltoSNR
=8dB;
the VTOL flight between the L and P points is
carriedoutataconstantaltitudehL=50mwitha
velocity v=72km/h=20m/s (see Figure 3); then,
theflightceilingislowered;
thelengthoftheanalyzedVTOLflightroute,i.e.,
thedistancebetweentheLandPpoints,isequalto
d=400m.
432
Table1.CoordinatesofRBpositionsonOXYplanefordifferentconfigurations
__________________________________________________________________________________________________
RB‐k ConfigurationofRBs
__________________________________________________________________________________________________
RegularTriangle SquareRegularpentagon Regularhexagon
K=3K=4K=5K=6
r=49.0mr=40.0mr=33.3mr=28.3m
__________________________________________________________________________________________________
k xk(m)yk(m)xk(m)yk(m)xk(m)yk(m)xk(m)yk(m)
1 14.1 24.5 20.0 20.0 22.9 16.6 24.5 14.1
2 14.1 –24.5  20.0 –20.0  22.9 –16.6  24.5 –14.1
3 28.3 0.0–20.0  –20.0  –8.7 –26.9 0.0–28.3
4 ––– ––– –20.0  20.0 –28.3  0–24.5  –14.1
5 ––– ––– ––– ––– –8.7 26.9 –24.5  14.1
6 ––– ––– –––
––– ––– ––– 0.028.3
__________________________________________________________________________________________________
Figure3. Spatial scenario of VTOL landing approach on
example of RB reference configurationprojectedin plane:
a)OXZandb)OXY[30]
Simulation studies are carried out for the UAV
movement trajectory depicted in Figure 3. In this
case, two scenarios are considered. In the first
scenario, Sc.1, we evaluate the VTOL position error
alongtheLPtrajectoryfordifferentRBconfigurations
and the approach direction α
=0. In the second
scenario,Sc.2,theVTOLpositioningerrorisanalyzed
atthepointPforthevariousαdirections.
4 RESULTSOFSIMULATIONSTUDIES
For the assumptions presented in Section 3, we
conducted simulation studies. In our analysis, the
VTOL positioning error is a basic measure of the
accuracy
assessment of the developed navigation
system.Thismeasureisdefinedasfollows

222
000
Δ
R
xx yy zz (1)
where(
x0,
y0,
z0)and(x,
y,
z)=therealandestimated
coordinatesoftheUAVposition,respectively.
The simulation results obtained for Sc.1 are
illustrated in Figure 4. In this case, graphs of the
instantaneouspositioningerrorfortheVTOLlanding
approach are presented for four analyzed RB
configurations. Additionally, the average errors
shownbydashed
lines.
Figure4. Instantaneous and average VTOL positioning
errors versus distance d to point P for various RBs
configurations:a)K
=3,b)K=4,c)K=5,andd)K=6
The obtained results show the high precision of
theVTOLpositioningbasedontheproposedsystem
and SDF method. For d
<100m, the instantaneous
error of the UAV position for each configuration is
lessthan1.0
m.Inthelastsecondofapproachingthe
pointP,theerrorislessthan0.5
m.
433
Figure5. VTOL positioning error at point P versus
approach direction α for different RB configurations:
a)K
=3,b)K=4,c)K=5,andd)K=6
InSc.1,wemayusetheaverageerrorobtainedon
theentireanalyzedroutewiththelengthof400
mas
a comparative measure. In this case, the average
errors are equal to 2.4
m, 3.8m, 3.4m, and 3.8m for
configurations based on the regular triangle,
rectangle, pentagon, and hexagon, respectively.
Therefore,wemayconcludethatthebestresultsare
obtainedforK
=3.Thisresultmayberelatedtothe
approach direction α
=0 assumed in Sc.1. Thus, for
oddvaluesofK,oneofRBisinthedirectionofthe
UAVmovement.
The impact of the VTOL approach direction
relativetotheadoptedcoordinatesystemisanalyzed
inSc.2.Theobtainedsimulationresultsareillustrated
inFigure5.
The obtained graph
shapes of the UAV position
error are closely related to the RB configurations
depicted in Figure 2. In this case, the largest errors
occurwhenthe approachdirectionαcoincides with
the direction determined by the point O and the
locationofatleastoneRB.Inthesignalreceivedfrom
such RB, the estimated DFSs take maximum values
and these data are not used in the SDF. This is
particularlyvisibleforK
=4andK=6,whenaRBpair
isalwayslocatedintheanalyzeddirections.
TheanalysisoftheresultsinFigure5showsthat
decreasingthenumberofRBsinthesystemdoesnot
necessarily lead to higher system accuracy. For
comparison of the individual configurations, the
errors at point P averaged over
the approach
direction are 0.76
m, 0.17m, 0.55m, and 0.16m for
K
=3,4,5,6, respectively. Therefore, this is the
oppositecasetothatpresentedinFigure4.
Generally, for each of the analyzed RB
configurations,theVTOLpositioningerroratpointP
isalwayslessthan2
mregardlessofthedirectionα.
Formostapproachdirections,theUAVpositionerror
is less than 0.5
m. These values are very small in
relation to the assumed radius of the landing pad
equaltoR
≈28.3m.Hence,wemayconcludethatthe
developed system allows the safe and autonomous
landing approach even withsizable dimensions of
theVTOL.
5 CONCLUSION
In this paper, we evaluate the influence of the RB
configurationinthelandingapproachsystemforthe
VTOL UAV on its positioning error. The developed
system is based on the DFS measurement in the
signals received from the terrestrial RBs around the
landingpad.TheDFSsaremeasuredinthededicated
NR, which is placed onboard aircraft. The SDF
method is used to estimate the VTOL position
relativetothelandingsite.Ouranalysisis
basedon
simulation studies. In this case, we consider two
scenarios and four RB configurations based on the
regularpolygons.Theobtainedresultshowsthehigh
accuracy of the UAV positioning for all analyzed
configurations. The best results at the point located
above the landing center are obtained for the
configuration
consistingofsixRBs.Atthispointand
for this configuration, the mean error regardless of
the approach direction was less than 20
cm. The
proposedsolutionseemsidealforuseinstand‐alone
autonomouslandingapproachsystemsfortheUAV.
However, empirical research is still required, which
isplannedinthefuture.
The presented idea of the SDF‐based navigation
for UAVs can also be used for the needs of other
types of
autonomous vehicles. In the future, we
considerusingthisconceptto navigate autonomous
USVsormannedvesselsenteringaport.Inthiscase,
theRBswillbelocatedinthecoastalzonearoundthe
port.
434
ACKNOWLEDGMENTS
This work was developed within a framework of the
Research Grant “Basic researchinsensortechnology field
using innovative data processing methods” no.
GBMON/13‐996/2018/WAT sponsored by the Polish
MinistryofDefense.
REFERENCES
[1]Groves,P.D. 2013. Principles of GNSS, inertial, and
multisensor integrated navigation systems, 2nd ed.
Boston,MA,USA:ArtechHouse.
[1]Tortonesi,M., Stefanelli,C., Benvegnu,E., Ford,K.,
Suri,N. & Linderman,M. 2012. Multiple‐UAV
coordination and communications in tactical edge
networks.IEEECommunicationsMagazine50(10):48–55.
[2]Orfanus,
D. deFreitas,E.P. & Eliassen,F. 2016. Self‐
organization as a supporting paradigm for military
UAV relay networks. IEEE Communications Letters
20(4):804–807.
[3]Ma’sum,M.A., Arrofi,M.K., Jati,G., Arifin,F.,
Kurniawan,M.N., Mursanto,P. & Jatmiko, W. 2013.
Simulation of intelligent unmanned aerial vehicle
(UAV) for military
surveillance. 2013 International
ConferenceonAdvancedComputer Science and Information
Systems(ICACSIS),Bali,Indonesia,28–29September2013:
161–166.
[4]Babak,S., Myslovych,M. & Sysak,R. 2016. Module
structure of UAV‐based computerized systems for
remote environment monitoring of energy facilities.
201617thInternationalConferenceComputationalProblems
of Electrical Engineering
(CPEE), Sandomierz, Poland, 14–
17September2016:1–3.
[5]Daliento,S., Chouder,A., Guerriero,P., Pavan,A.M.,
Mellit,A., Moeini,R. & Tricoli,P. 2017. Monitoring,
diagnosis,andpowerforecastingforphotovoltaicfields:
A review. International Journal of Photoenergy
2017(e1356851):1–13.
[6]Quater,P.B., Grimaccia,F., Leva,S. Mussetta,M. &
Aghaei,M. 2014. Light unmanned aerial vehicles
(UAVs) for cooperative inspection of PV plants. IEEE
JournalofPhotovoltaics4(4):1107–1113.
[7]Grimaccia,F., Aghaei,M., Mussetta,M., Leva,S. &
Quater,P.B. 2015. Planning for PV plant performance
monitoring by means of unmanned aerial systems
(UAS).International Journal of Energy and
Environmental
Engineering6(1):47–54.
[8]Berni,J.A.J., Zarco‐Tejada,P.J., Suarez,L. & Fereres,E.
2009. Thermal and narrowband multispectral remote
sensing for vegetation monitoring from an unmanned
aerialvehicle.IEEETransactionsonGeoscienceandRemote
Sensing47(3):722–738.
[9]Wijitdechakul,J., Sasaki,S., Kiyoki,Y. & Koopipat,C.
2016. UAV
‐based multispectral image analysis system
with semantic computing for agricultural health
conditionsmonitoringandreal‐timemanagement.2016
International Electronics Symposium (IES), Denpasar,
Indonesia,29–30September2016:459–464.
[10]Yuan,C.,Liu,Z.,&Zhang,Y.2016.Vision‐basedforest
fire detection in aerial images for firefighting using
UAVs. 2016
International Conference on Unmanned
AircraftSystems(ICUAS),Arlington, VA,USA,7–10June
2016:1200–1205.
[11]Ghamry,K.A., Kamel,M.A. & Zhang,Y. 2016.
Cooperativeforestmonitoringandfiredetectionusinga
team of UAVs‐UGVs. 2016 International Conference on
UnmannedAircraftSystems(ICUAS),Arlington,VA,USA,
7–10June2016:1206–1211.
[12]Rathinam,S., Almeida,P., Kim,Z., Jackson,S.,
Tinka,A., Grossman,W. & Sengupta,R. 2007.
Autonomoussearchingandtrackingofariverusingan
UAV.2007AmericanControlConference(ACC),NewYork,
NY,USA,9–13July2007:359–364.
[13]Popescu,D., Ichim,L. & Caramihale,T. 2015. Flood
areasdetectionbasedonUAVsurveillancesystem.2015
19th International Conference on System Theory,
Control and Computing (ICSTCC), Cheile Gradistei,
Romania,14–16October2015:753–758.
[14]Lu,Y. Macias,D. Dean,Z.S., Kreger,N.R. &
Wong,P.K.2015.AUAV‐mountedwholecellbiosensor
systemforenvironmentalmonitoringapplications.IEEE
TransactionsonNanoBioscience14(8):811–817.
[15]Erdos,D., Erdos,A. & Watkins,S.E. 2013. An
experimental UAV system for search and rescue
challenge. IEEE Aerospace and Electronic Systems
Magazine28(5):32–37.
[16]Mozaffari,M.,Saad,W.Bennis,M.&Debbah,M.2017.
Optimal transport theory for cell association in UAV‐
enabled
cellularnetworks.IEEE Communications Letters
21(9):2053–2056.
[17]Hoareau,G., Liebenberg,J.J., Musial,J.G. &
Whitman,T.R.2016.Packagetransportbyunmannedaerial
vehicles.PatentUS20160068265A1.
[18]Towards a European strategy for the development of
civilapplicationsof RemotelyPiloted AircraftSystems
(RPAS). 2012. Brussels, Belgium: Council of the
EuropeanUnion.
[19]vanBlyenburgh,P.2012.TowardsaEuropeanstrategy
forthedevelopmentofcivilapplicationsofRPAS.UAS
Vision.Available:
https://www.uasvision.com/2012/09/07/towards‐a‐
european‐strategy‐for‐the‐development‐of‐civil‐
applications‐of‐rpas/
[20]Duszczyk,M.2017.Forecastsforthedronemarketare
promising (inPolish). Rzeczpospolita, Available:
https://www.rp.pl/Sylwetki/303209855‐Prognozy‐dla‐
rynku‐dronow‐sa‐obiecujace.html.
[21]Kaplan,E.D. & Hegarty,C. (eds). 2005. Understanding
GPS: Principles and applications, 2nd ed. Boston, MA,
USA:ArtechHouse,2005.
[22]vanDiggelen,F.2009.A‐GPS:AssistedGPS,GNSS,and
SBAS.Boston,MA,USA:ArtechHouse,2009.
[23]Kayton,M. &
Fried,W.R. 1997. Avionics navigation
systems, 2nd ed. New York, NY, USA: Wiley‐
Interscience.
[24]Kelner,J.M., Ziółkowski,C. & Nowosielski,L. 2016.
LocalnavigationsystemforVTOLsusedonthevessels.
2016 IEEE/ION Position, Location and Navigation
Symposium (PLANS), Savannah, GA, USA11–14 April
2016:415–421.
[25]Kelner,
J.M., Ziółkowski,C. & Kachel,L. 2008. The
empirical verificationof the locationmethodbased on
thedopplereffect. 2008 17th International Conference on
Microwaves, Radar and Wireless Communications
(MIKON),Wrocław,Poland,19–21May2008.vol.3:755–
758.
[26]Kelner,J.M. 2010. Analysis of the Doppler location
method
of the radio waves emission sources, Ph.D.
Thesis(inPolish).Warsaw,Poland:MilitaryUniversity
ofTechnology.
[27]Gajewski,P.,Ziółkowski,C.&Kelner,J.M.2012.Using
SDFmethodforsimultaneouslocationofmultipleradio
transmitters. 2012 19th International Conference on
MicrowaveRadar andWirelessCommunications(MIKON),
Warsaw,Poland,21–23
May2012.vol.2:634–637.
[28]Kelner,J.M. 2011. Positioning an aircraft using the
TDSDF method. Polish Journal of Environmental Studies
20(5A):80–84.
[29]Kelner,J.M. & Ziółkowski,C. 2011. The concept of
Doppler Landing Approach Precision System
(DOLAPS) Polish Journal of Environmental Studies
20(5A):85–90.
[30]Kelner,J.M.
& Ziółkowski,C. 2017. Doppler effect‐
basedautomaticlandingprocedureforUAVindifficult
accessenvironments.Journal of Advanced Transportation
2017(e8092718):1–9.
435
[31]Kelner,J.M., Ziółkowski,C. & Marszałek,P. 2016.
Influence of the frequency stability on the emitter
position in SDF method. 2016 17th International
Conference on Military Communications and Information
Systems(ICMCIS),Brussels,Belgium,23‐24 May 2016:1–
6.
[32]Grayver,E. 2012. Implementing software defined radio.
NewYork,NY,USA:Springer.
[33]Mitola,J. 2000. Software radio architecture: object‐
oriented approaches to wireless systems engineering.
NewYork,NY,USA:Wiley.
[34]Kelner,J.M. & Ziółkowski,C. 2015. The use of SDF
technology to BPSK and QPSK emission sources’
location (inPolish). Przegląd Elektrotechniczny 91(3):61–
65.
[35]Stefański,J. 2015. Asynchronous time difference of
arrival (ATDOA) method. Pervasive and Mobile
Computing23:80–88.
[36]Sadowski,J.&Stefański,J.2017.Asynchronousphase‐
location system. Journal of Marine Engineering &
Technology16(4):400–408.