,*
1.The Science and Technology on UAV Laboratory,Northwestern Polytechnical University,Xi’an 710065,China;2.College of Marine Science and Technology,Northwestern Polytechnical University,Xi’an 710065,China
Multi-dimensional and complicated electromagnetic interference hardware-in-the-loop simulation method
Shuxia Guo1,Yafeng Wang1,*,Ruibing Liu1,and Ying Gao2
1.The Science and Technology on UAV Laboratory,Northwestern Polytechnical University,Xi’an 710065,China;
2.College of Marine Science and Technology,Northwestern Polytechnical University,Xi’an 710065,China
A typical electronic communication system,such as GPS receiver,unmanned aerial vehicle’s(UAV’s)data link,and radar,faces multi-dimensional and complicated electromagnetic interference in operating environment.To measure the antiinterference performance of the electronic communication system in the complicated electromagnetic interference environment,a method of multi-dimensional and complicated electromagnetic interference hardware-in-the-loop simulation in an anechoic room is proposed.It takes into account the characteristics of interference signals and the positional relationship among interference,the receiver and the transmitter of the electronic communication system. It uses the grey relational method and the angular domain mapping error correction method to control the relevant parameters, the microwave switch and so on,thus achieving the approximately actual mapping of the outdoor multi-dimensional and complicated electromagnetic interference in the anechoic room.To verify the effectiveness of this method,the multi-dimensional and complicated electromagnetic interference of the UAV’s data link is simulated as an example.The results show that the degree of correlation between the calculated signal to interference ratio of the data link receiver in the actual scene and the measured signal to interference ratio of the data link receiver simulated with this method in the anechoic room is 0.968 1,proving that the method is effective for simulating the complicated electromagnetic interference.
electromagnetic interference,hardware-in-the-loop simulation,grey relational method,scene mapping,correlation error correction.
A typical electronic communication system faces multidimensional and complicated electromagneticinterference which is dynamic,time-variant,diverse and multi-level. Therefore,it is imperative not only to test whether it satisfie its electromagnetic compatibility but also to consider its adaptability under the complicated electromagnetic interference environment[1].Taking an unmanned aerial vehicle(UAV)for example,its data link is an important component for information transmission between the UAV and its ground station,as the requirements for its reliability and security are higher and higher,the requirements for its electromagnetic environment adaptability are also increasing[2].Taking a GPS receiver for another example,there are higher requirements for its strong electromagnetic interferenceresistance as the requirements for its positioning accuracy is higher[3–5].That is why it is necessary to explore the complicated electromagnetic interference simulation method and measure the electronic communication system’s adaptability in the external electromagnetic interference environment[6].
Anechoic Chamber and Reverberation Chamber are both typical radiation test sites,but the former can effectively absorb electromagnetic wave reflection To avoid affectingthe accuracyand repeatabilityof measurement,it is more suitable for the anti-interference testing of the electroniccommunicationsystem thanthe reverberationchamber under the electromagnetic interference environment.
Currently,the fi ed antenna is often used to simulate electromagnetic environment.Fixed wireless propagation environments including effects such as narrowband fading and Doppler spread in an anechoic room were simulated in[7].Plane waves were used in[8],which have the fi ed direction of arrival and random variation magnitudes,and they were superimposed to form the electromagnetic interference environment;because the direction of the plane waves was fi ed,there is no way to truly simulate the distribution of electromagnetic interference.Several radiation antennas were placed in[9],whose interference was f xed at different locations surrounding the wireless equipment to be tested in an anechoic room so as to simulate the locational relationship between interference and the wirelessequipment,aiming to manifest the degree of influenc of different electromagnetic interference radiation directions on the performance of the wireless equipment.However, when the wireless equipment is in motion state,the simulation method cannot simulate the locational relationship betweeninterferenceand the wireless equipment,affecting the authenticity of the simulation.In terms of simulating the dynamic interference,the location and velocity of the interferenceradiation antenna with a slide rod motion control system were controlled in[10]to simulate the motion state of interference.However its weakness was that the motion of the slide rod between two locations took some time,making it difficul for the radiation of interference signals to be synchronous with the simulation steps and causing simulation time-sequential chaos.
To measure the anti-interference performance of the electronic communication system in the electromagnetic interference environment,the method of the multidimensional and complicated electromagnetic interference hardware-in-the-loopsimulation in an anechoic room is proposed.Hardware-in-the-loop simulation is a technique that connects controllers with the simulation model implemented in a computer and reflect the dynamic characteristics of controllers by adding a mathematical representation.It is very efficien and economic for the simulation of electromagnetic interference.In Section 2,the multi-dimensional and complicated electromagnetic interference model is established to calculate the signal to interference ratio(SIR)of the receiver of the electronic communicationsystem in the complicatedelectromagnetic interference environment.In Section 3,the scene mapping method based on grey relational and the scene mapping error correction method are explained and the instrument drive method based on scenarios is used to produce interference signals.In Section 4,the multi-dimensional and complicated electromagnetic interference is simulated through setting the simulation scene and simulation parameters to verify the effectiveness of the method.
As shown in Fig.1,there are n number of interferences in the complicatedelectromagneticenvironment,so the receiver of the electronic communication system is used as the point of origin to establish the rectangular space coordinates.The distance from interference i to the receiver is Ri;the azimuth and the pitch angle of receiver relative interferenceare φiandθi,respectively;the distance fromthe transmitter to the receiver is R0;and the azimuth and the pitch angle are φ0and θ0,respectively.
Fig.1 Multi-dimensional and complicated electromagnetic interference
If the modulation signal of interference i is mi(t);the direction of fiel strength polarization is vEiand perpendicular to the direction of incidence vi;the direction of magnetic fielis vHiand perpendicular to the planes of vEiand vi;the frequency of interference is fi;its initial phase is αi;if vi=(cosθicosφi,?cosθisinφi,sinθi), then the electric fieland the magnetic fieldistribution Eiand Hiof interference i are expressed respectively as follows:
where i=1,2,....PTiand GTidenote the transmission power and the antenna gains of the ith interference respectively.Eimand Himdenote the peak of the electric and magnetic fiel respectively.Ridenotes the propagation distance of the ith interference signal.η0denotes the impedance η0= 120π of a free space wave.c is the space electromagnetic wave transmission speed and c=3.0×108m/s.
The total mean power density for n number of interferences to arrive at the receiver of the electronic communication system is thus obtained as follows:
Therefore,the total power for the nth interference to arrive at the receiver is
If the power for the signals transmitted by the electronic communication system to arrive at the receiver is P0,then the SIR of the receiver is
Equations(1)–(5)can thus calculate the SIR of the receiver.
The multi-dimensional and complicated electromagnetic interference in actual scene is shown in Fig.2(a).To simulate the complicated electromagnetic interference,the hardware-in-the-loopsimulation platformis constructedas shown in Fig.2(b).
Fig.2 Actual scene and hardware-in-the-loop simulation scene mapping
In Fig.2(a),the angleE(n)between the current interferenceΓ(j)and the connection line of the receiver and transmitter can be expressed as
whereaj,bj,cjdenote respectively the current distance from the receiver to the transmitter,the distance from the receiver to the interferencejand the distance from the transmitter to the interferencej.
In Fig.2(b),it shows that the simulation control computer in the simulation platform controls different models of microwave instrument and microwave switch respectively to produce the different interference signals and select theirradiationantennas.Toachievetheoptimalmatching betweeninterferenceandradiationantennas in the anechoic room,it is imperative to determine in real time the angular domain and locational relationship among the interferenceand the receiverand transmitterof the electronic communication system.
3.1Multi-dimensional and complicated electromagnetic interference scene mapping method
The grey relational method[11,12]was widely applied in data processing.According to the theory,first determine the data sequence of one leading variable(main control factor)and that of several secondary variables(influenc factors).Then,calculate their respective correlation coefficient between the influenc factor and the main control factor,thereby distinguishing the degree of correlation between different influenc factors.
If the data sequence consisting of the angle between the direction of the main wave lobe ofnnumber of radiation antennas and the connection line of the receiver and transmitter of the electronic communication system is the main control factor,then it is expressed asE(n);if the angle betweenjnumber of interferences of the operating receiver and the connection line of the receiver and the transmitter iswheredenotes the angle between interferencekand the connection line of the receiver and the transmitter.To makeE(n)dimensionally consistent withΓ(j),it is imperative to addn?jnumber ofthus obtainingAccording to permutation and combination,H?(n)is obtained with the permutation ofΓ(n)and used as the sequence of influenc factors,where?=Ajndenotes the number of permutations of the angle between interference and the connection line of the receiver and the transmitter.Γi(n) is used to denoteigroup of permutationsΓ(n);and the obtained angular domain relationship is
where[·]Tdenotes the sequence of the matrix.
To achieve the approximately actual mapping of the multi-dimensional and complicated electromagnetic interferencefromoutdoorto indoor,the fi ed angleE(n)in(7) is used as the data sequence of the main control factor andH?(n)is used as the data sequence of the influenc factor. The grey relational method is used to calculate the degree of correlationH?(n)andE(n).The procedural steps can be shown as follows.
Step 1Select the main factor sequence,namely the angleE(n)between the indoor radiation antenna and the connection line between the receiver and the transmitter, and then make it dimensionless.
wherendenotes the number of radiation antennas;denotes the dimensionless main factor sequence.
Step 2Select the influenc factor sequence,namelyH?(n),and make each group ofΓi(n)inH?(n)dimensionless.
Step 3Calculate correlation coefficient
Step 4Average correlation coefficient
In the paper,it is assumed that the angle between the Interference 1 and Interference 2 in the actual scene and the receiver of the electronic communication system isα. After grey relational,the antennajradiates Interference 1 and the antennairadiates Interference 2.The angle between the radiation antennasiandjand the receiver to be simulated isβ.However,owing tothere is thus causing angular domain corre-spondence errors as shown in Fig.3.Because of these errors,the simulation precision may be affected in a certain degree.Therefore,the correlation error correction method is proposed.
Fig.3 Relationship among angular domains after grey relational
3.2Correlation error correction method
According to Fig.3,in the actual scene,if the power of Interference 1 isp1and Interference 2 isp2when arriving at the apertural face of the receiver’s antenna at thetmoment,then the compoundpower of the two interferencesis obtained as follows:
In the anechoic room,if the power of the emission antennaiispiand that ofjispjwhen arriving at the apertural face of the receiver’s antenna at thetmoment,then the compoundpowerofthetworadiationsourcesis as follows:
Ifpj=p2ands1=s2,joining(12)and(13)can produce
Therefore,the radiation antennasiandjtransmit their interferencesignalsat thepowersofpiandpj.At thistime, thepowersynthesizedbythereceiverindoorsequalstothat synthesized by the receiver at the outside.The constant adjustment of the power of interference signals produces the interference signals that correspond to those in the actual scene.Therefore,to produce the interference signals,the multi-dimensional and complicated electromagnetic interference of the receiver was simulated indoors with a microwave instrument drive.
3.3Instrument drive method based on scenarios
It is assumed that the time needed for the receiver of the electronic communication system to move from the current position to the next one within one simulation step is Δt.The simulation of the interference of the receiver atthe current position requires that the timetneeded by the drive instrument should be as less as possible and satisfyt≤Δt.In addition,the simulation of the interference of the receiverin differentscenes requiresthe differentequipment for simulating interferencesignals.Therefore,the selectionofafast andintelligentinstrumentdrivewithstrong expandabilityis crucial for simulating the complicatedand dynamic electromagnetic interference,as shown in Fig.4.
Fig.4 Instrument drive method
In Fig.4,in case of several instruments,the instrument drive method only requires the control program to read the drive file of different instruments and send them to the instruments.As a result,the method only needs to execute the control program and read scenario file instead of executing extra codes,thus enhancingthe executionefficien y of the electronic communicationsystem,reducingthe time needed by its drive instrument and laying the foundation for constantly adjusting the magnitude and phase of an interference signal.Besides,when another interference signal simulation equipment is added,the method only needs to compile the drive file of the drive instrument according to the uniform format and employ the drive file with the control program,thus realizing the drive of the newlyadded simulation equipment and greatly enhancing the expandability of the electronic communication system.
4.1Setting the scene
The hardware-in-the-loop simulation platform is constructed with the electromagnetic interference simulation method proposed in the above.Eight radiation antennas (marked 1 through 8)are laid in an anechoic room.They have the same characteristics as the interference radiation antennas in the outdoor scene.The direction of the transmitter’s antenna can be adjusted by locating the direction of its main wave lobe along the same straight line as the connection line between the receiver and the transmitter. The receiver’s antenna here is an omnidirectional antenna. The angle between the direction of the radiation antenna’s main wave lobe and the connection line between the receiver and the transmitter to be simulated in the anechoic room isE(8)={14.90,24.80,34.50,45.30,54.80,650, 74.90,84.30}.The hardware-in-the-loop simulation platform was used to set the receiver simulation scenes that include transmitter,receiver,Interferences 1 and 2,and then set the receiver’s operation trajectory to be 30 simulation moments and the simulation stepping time to be 100 ms, as shown in Fig.5.
Fig.5 Setting scenes
4.2Setting simulation parameters
Takingthe data linkof a UAV foranexample,the transmitter at the groundstation is used as the originof coordinates toestablishitsrectangularspacecoordinates.Iftheantenna of the UAV’s data link receiver is omnidirectional,signal bandwidthisB=10 MHz,andthefrequencyisf=2.0 GHz, then the real-time coordinates of the receiver are expressed as(x,y,z).
Simulation parameters are set as in Table 1.
Table 1 Simulation parameters
In Table 1,the incidence directions arev1=(x?3.2,y?2.4,z),v2=(x?4.1,y?5.2,z)andv0= (x,y,z).The perpendicularity between polarization direction and signal incidence direction aree1=(2.4?y,x?3.2,0)/|v1|,e2=(5,2?y,x?4.1,0)/|v2|ande0=(?y,x,0)/|v0|.
4.3Analysis of simulation results
At each simulation moment,the receiver’s coordinates change constantly.Equation(6)is used to calculate in real time the angle between the two interferences and the connection line of the UAV’s data link receiverβj.However,as the receiver’s coordinates change,βjalso changes constantly.Equations(7)–(11)can produce the maximal correlation coefficien max(βj)at each moment,as shown in Fig.6.
Fig.6 Grey relational results
Fig.6 shows that themaximalcorrelationcoefficien between the outdoor interference of the UAV’s data link receiver and the simulation scene inside the anechoic room changes constantly.min(βj)=0.787,max(βj)=0.947.
With the correlation coefficient given in Fig.6,the onoff switching mode is selected that corresponds to each moment,as shown in Fig.7.
Fig.7 On-off switching mode at each moment
Fig.7 shows that the mapping from the two interferences at the actual scene to the radiation antennas in the anechoic room changes constantly within the simulation time.At the 10th simulation moment,Interference1 corresponds to the 4th radiation antenna in the anechoic room; Interference 2 corresponds to the 6th radiation antenna.
According to the on-off switching mode obtained at each moment,the FSQ-26 spectral analyzer is used to read separately the power of a single interference at each moment before and after the angular domain mapping error correction and then compare it with the calculation value, as shown in Fig.8.
Fig.8 Curve of power at each moment
Fig.8 shows that the power needed for the two interferences obtained with the grey relational method and simulated in an anechoic room to arrive at the receiver is in the basic agreement with the calculated power at the actual scene.Moreover,the power obtained after the angular domain mapping error correction is more approximate to both the simulated and calculated values than that before the correction.
Equations(1)–(5)are used to calculate the SIR of outdoor interference signal that arrives at the receiver,as shown in Fig.9.
Fig.9 SIR of outdoor interference signal
The calculated SIR of the signal at the actual outdoor scene is selected as the main control factor and the measured SIR at each moment before and after angular domain mapping error correction in the anechoic room are selectedas influenc factorsto calculate thedegreesof correlation between the main control factor and the influencfactors with(7)–(11),which is being 0.784 2 and 0.968 1 respectively before and after angular domain mapping error correction.Thus,the degrees of correlation before and after angular domain mapping error correction are raised by 0.1839,indicating that the angular domainmappingerror correction method is effective and that the actual scene mapping is approximately authentic.Moreover,the grey relational results given in Fig.6 show that the minimal degree of correlation between the actual interference of the receiver of the electronic communication system and the scene simulated in the anechoic room is 0.787,whose difference from the SIR in Fig.9 is only 1.914 9,indicating that the anechoic room simulation and the actual scene are essentially consistent.During the error correction,the dynamic drive time of the microwave instrument always remains around 10 ms and the simulation step is always 100 ms,revealingthat the instrument drivetime fully meets the requirements for the error correction.
To measure the adaptability of the electronic communication system in electromagnetic environment,the authenticity principle is followed and the methods,like grey relational method,the angular domain mapping error correction method,are used to control the relevant parameters of several interferences,the microwave switch and so on,thus achieving the approximately actual mapping of the outdoor multi-dimensional and complicated electromagnetic interference in the anechoic room.The methodin this paper could achievethe dynamicsimulation of complex electromagnetic interference environment and get more benefit comparedwith other outdoor simulation. It canbeused innot onlythe electronicinformationsystem testing,but also the military training and electromagnetic environment effects research.
[1]F.Wan,F.Duval,X.Savatier.Electromagnetic interference detection method to increase the immunity of a microcontrollerbased system in a complex electromagnetic environment.IET Science Measurement&Technology,2012,6(4):254–260.
[2]J.A.Yochim.The vulnerabilities of unmanned aircraft system common data links to electronic attack.Master of Military Art and Science,2010.
[3]S.Dinesh,M.Faudzi,M.M.Z.Fitry.Evaluation of the effect of radio frequency interference on global positioning system (GPS)accuracy via GPS simulation.Defence Science Journal, 2012,62(5):338–347.
[4]C.W.Rhodes.Interference to digital broadband communications and spread spectrum communications.IEEE Trans.on Consumer Electronics,2012,58(1):15–22.
[5]M.J.Marcus.Observations on the US MSS/GPS Interference Controversy.IEEE Wireless Communications,2012,19(1):6–7.
[6]D.Lu,R.B.Wu,H.T.Liu.Global positioning system antijamming algorithm based on period repetitive CLEAN.IET Radar Sonar and Navigation,2013,7(2):164–169.
[7]K.A.E.Genender,H.G.Remley.Simulating the multipath channel with a reverberation chamber:application to bit error rate measurements.IEEE Trans.on Electromagnetic Compatibility,2010,52(4):766–777.
[8]C.James,C.F.B.West.Accurate and efficien numerical simulation of the random environment within an ideal reverberation chamber.IEEE Trans.on Electromagnetic Compatibility,2012,54(1):167–173.
[9]M.D.Foegelle.The masters of MIMO:creating a complex multipathenvironment simulationin an anechoic chamber.Microwave Journal,2010,53(8):56–64.
[10]T.Noguchi,S.I.Demura,T.Nakagawa.Postural stability during one-leg stance on an unstable moving platform and its relationship with each leg.Perceptual and Motor Skills,2013, 116(2):555–563.
[11]Y.Y.Kuo,T.H.Yang,G.W.Huang.The use of grey relational analysis in solving multiple attribute decision-making problems.Computers&Industrial Engineering,2008,55(1): 80–93.
[12]Z.H.Hu,M.Zhao,M.Yao.Multi-objective and multiconstrained UAV path plan optimum selection based on GRA.Journal of Grey System,2011,23(1):35–46.
Shuxia Guowas born in 1965.She received her B.S.degree from Shenyang Science and Technology University in 1986,M.S.degree in communication from Xidian University in 2002 and Ph.D. degree in communication and information systems from Northwest Polytechnical University in 2008. From 1986 to 1999,she worked in Northwest Institute of Electrical and Mechanical Engineer as a senior engineer.Now she is an associate professor in Science and Technology on UAV Laboratory in Northwestern Polytechnical University. Her research interests are wireless communications and complex electromagnetic environment simulation.
E-mail:guoshuxia0223@163.com
Yafeng Wangwas born in 1990.He is an M.S.degree candidate in Northwestern Polytechnical University.His research interests are wireless communications and complex electromagnetic environment simulation.
E-mail:wyf5529185@163.com
Ruibing Liuwas born in 1989.He is an M.S.degree candidate in Northwestern Polytechnical University.His research interests are satellite navigation and complex electromagnetic environment simulation.
E-mail:495942804@qq.com
Ying Gaowas born in 1965.He is a Ph.D.and an associate professor in Northwestern Polytechnical University.His research interests are system simulation,virtual reality&multimedia and visualization analysis.
E-mail:gaoying@nwpu.edu.cn
10.1109/JSEE.2015.00124
Manuscript received October 28,2014.
*Corresponding author.
This work was supported by the National Natural Science Foundation of China (61571368) and the certain Ministry Foundation (2014607B006).
Journal of Systems Engineering and Electronics2015年6期