Systems Approach To Ground Vehicle Electromagnetic .
2010 NDIA GROUND VEHICLE SYSTEMS ENGINEERING ANDTECHNOLOGY SYMPOSIUMVEHICLE ELECTRONICS & ARCHITECTURE (VEA) MINI-SYMPOSIUMAUGUST 17-19 DEARBORN, MICHIGANSystems Approach to Ground Vehicle ElectromagneticCompatibilityRandolph Beltz – Sr. Principle Systems Engineer, BAE SystemsDr. Bandon Hombs – Sr. Signal Processing Engineer, BAE SystemsWilliam Mouyos -Technology Development Manager, BAE SystemsABSTRACTBAE Systems has developed a system level approach for identifying the issuesassociated with collocating Blue Force Communications with other on-boardemitters. Specific scenarios include broadband interference caused by ElectronicWarfare (EW) and radio congestion. Our approach is divided into three (3)functional areas to resolve this complex situation: (1) the proper selection andplacement of Advanced Antenna Structures. (2) Receiver front end overloadingprotection through the use of a Wide Band Frequency Domain CancellationAnalog/Digital RF cancellation process. (3) The further refinement of the signalthrough the use of Digital Signal Processing for interference estimation, tracking,and cancellation based on efficient adaptive algorithms.INTRODUCTIONGround Vehicle Topside RF integrationcontinues to grow in complexity as moresensors, communication channels and selfprotection systems are required for today’s warfighting. To aggravate the situation, vehicles invery close proximity to each other causeadditional mutual self-interference.This paper describes a methodology formitigating RF interference though the use ofsystem engineering practices directed atreducing coupling affects, understanding theinterference sources and using processingto improve performance.
Although some solutions are suggested, it is not the intent of this paper to definesolutions but to suggest a course of action to describe and understand groundvehicle interference (cosite).(1) PROPER ANTENNA SELECTION AND PLACEMENTThe first stage of resolving the complex issues associated with collocating BlueForce Communications with other on-board emitters is through the use of variousantennas; ranging from Multi-Band Antennas (MBA) to distributed ArmorEmbedded Antennas (AEA). These antennas can provide omni-directionalcoverage, sectorized coverage or when phase properly can create far field nullswhich aids in low probability of detection and jamming. This section will discussthe system approach associated with the implementation of antennas on groundvehicles.The key to a total antenna system that is used for communications, electronicwarfare and signal intelligence is to maintain adequate isolation between eachfunction so the systems do not interfere with each other.Through the use of Electromagnetic (EM) modeling and simulation installedantenna performance can be predicted. In a typical scenario antennas areinstalled on a platform and the far field radiation patterns are predicted. Todetermine the near field antenna to antenna coupling is much more complicatedthan modeling of the far field. For this reason physical measurement of theantenna to antenna coupling is also performed to get accurate data. This data isused in the total system analysis to predict system performance prior to fieldingof the system. Various antenna types can assist in increasing the isolationbetween functions. For omni-directional coverage Multi-Band Antennas (MBA)are ideally suited and when coupled with sectorized or directional antennas suchas Armor Embedded Antennas (AEA) multiple function within the same band ofoperation can exist simultaneously.With today’s modern ground vehicles the “real estate” to install antennas islimited. By utilizing MBA’s that support more than a single frequency band ofoperation, the number of antennas can be minimized. Today’s MBA’s arecapable of covering from VHF to S-Band (27-6,000 MHz) in a single antennastructure. These antennas have been implemented on the Brigade CombatTeam Modernization (BCTM) program with great success.Some keyperformance parameters of MBA’s are: Improved isolation between CREW andCommunications, Improved Field of View (FOV) over existing systems, reducedvisual signature and Improved Frequency Coverage. These MBA’s provide theomni-directional coverage that is required for most communication waveforms;such as SINCGARS, EPLRS, WNW, SRW, HAVEQUICK and JTIDS.MBA’s when couple with AEA’s, provide optimal system performance. The needfor an armor embedded or conformal antenna solution comes from the desire to
have antennas with a low signature (Radar Cross Section - RCS and visual) sothe antennas do not distinguish the platforms function. Additionally, by installingantennas on the side of a platform the isolation between functions can beincreased which mitigates the cosite issues with multiple functions within thesame band of operation. The cosite between communications and counter IED isa major issue today. Current counter IED systems produce cosite interference byinadvertently jamming own-vehicle communications. Placing armor embeddedantennas on the sides of the vehicles helps isolate the counter IED transmissionsfrom communications antennas resulting in reduced cosite interference. Anarmor embedded antenna solution supports a directional or distributed jammingcapability and enhances the platform survivability. Having these antennaembedded into the armor provides an optimal balance between systemperformance and survivability.Figure 1: Armor Embedded Antenna BenefitsThe applications for an armor embedded antenna solution can cover anydirectional system requirement. Direction Finding Emitter Mapping Systems,directional Jamming Systems, Combat Identification Systems and directionalCommunications Systems all can be implemented in armor embedded systems.The key factors that make armor embedded antennas attractive are similar to thestructural embedded antennas implemented on aircraft. The size and weightimpacts to the platform can be minimized and the signature (both visual andRCS) can be reduced. By having the armor encompass both the armor andantenna functions, the antenna system survivability is increased while minimizingthe weight impact. Another clear benefit is that prime real estate, which iscurrently not utilized for antenna integration, can be taken advantage of with theembedding of the antennas in the armor.The exact implementation of armor embedded antenna is platform specific justas it is on aircraft. Through electromagnetic modeling and testing, the solutionthat provides the best compromise between all the key performance parameterscan be reached. By having armor embedded antennas and antennas such asMBA’s (whip type), the tools are in place to provide the platforms with the optimalconfiguration to meet the performance requirements.
BAE Systems’ approach to covering from VHF to UHF (30-450 MHz) entailspopulating the vehicle with several armor embedded panels and feeding to obtainthe desired pattern. The trade space includes how to phase the antennas toobtain the best pattern within the real estate on the platform and the antennaperformance.VHFUHFFigure 2: Directional Broadside Radiation PatternThe initial modeling shows that a directional pattern is formed by arrayingmultiple AEA’s as shown in Figure 2.(2) RECEIVER FRONT END OVERLOADING PROTECTIONReceiver front end overloading, which is referred to as Cosite interference occurswhen the reception of a desired signal is degraded due to one or more platformtransmitters radiating at the same time. The principle co-site characteristicstypically studied are shown below in Figure 3 .ZPlatform BodyGainGainNear fieldNear dulationData RateTransmitterAccess Method1dBCompressionInterference/CancellerData RateSpuriousEmissionsAccess MethodReceiverThermal equencyBandModulationFigure 3: RF Characteristics used in cosite study
The key sources of platform Cosite interference are: Transmitter Power Level– Tx Carrier Power causes Gain Compression and Desensitization inReceivers, ahead of any Filtering– Automatic Gain Control (AGC) Capture Wideband Thermal Noise Floor– Transmitter Noise is a Broadband Additive Noise Jammer over awide Frequency Range Transmitter Spurious– Unintentional Modulation of Carrier by Leakage Signals such asClock Harmonics, Synthesizer Reference Harmonics, SwitchClosures and Openings, Digital Noise appearing at DiscreteFrequencies Back Intermodulation– Special Case where High Power Signals impinge on the output ofanother Power Amplifier - It may cause the PA to go non-linear When this happens, IM products will be generated Rusty Bolt– Interference can be generated in the Environment when 2 or moreHigh Level Signals impinge on any object which cause NonlinearInteractions of the SignalsUnderstanding the ProblemA properly developed Cosite interference analysis model accounts for allinterference effects, including transmitter spectral power, reciprocal mixing,cross-modulation, Inter-modulation Distortion (IMD), transmit noise and receiverdesensitization as well as second order affects caused by the platform itself. Themodel provides characterization of interference between communications, radarand sensor source/victim pairs. All communications and non-communicationslinks are identified, including emitters and receivers, the signal format (waveform)and propagation medium. The location of the platform antennas and the coupling(or isolation) is also incorporated. Finally, understanding how the communicationlinks and sensors is used in an operational scenario is determined along with theLink quality needed for each signal format.
LRM GAIN/LOSS Specified MeasuredANTENNA GAIN Simulated Performance Measured PerformanceSIMULINK: LINK RANGE RF System Chain Analysis PATH LOSS RF Link AnalysisCABLE LOSS Calculated MeasuredLink Range Computations arecompared to KPP’s and PCD rangesLINK DRIVERS NOISE C/N BER TerrainFigure 4: RF Systems Analysis Context Diagram (Inputs and Outputs ofSimulation)The technical objective for the cosite analysis includes understanding thelimitations in system performance caused by the cosite interference problem,determining the dominant cosite effects that would degrade system performance,modeling system performance under cosite conditions, and generatingrecommendations to integrate the cosite mitigation schemes into the systemdesign taking into consideration the worst case platform deployment.Process and ToolsUnfortunately, there aren’t readily available tools for a RF topside platformintegrator to go to. The current tools (or analysis services) have been developedfor a specific application and do not have the flexibility to address varyinginstallations. BAE Systems has developed a suite of tools and subject matterexperts who have been working ground based communications for many years.PCD- WLS- RangeReview RFrequirements for:1- Waveforms2- Link RangesReview waveformspecs for BER, Eb/No,coding characteristics,etc.ReviewWaveformSpecsReviewspecs forGMR andFCS LRM’sRadio LRMSpecsAnalyze Tx & Rxparameters withLRM specs foreach RF pathRF ChainAnalysisUtilize the outputsfrom the RF ChainAnalysis, waveformcharacteristicsRF LinkAnalysisCo-site Noisefeedbackto designCo-site noise leveldetermined from LinkAnalysisTestsTest to validatedesign & analysis. LRM, SIL, FieldProvide feedback toboth Analysis andLRM needsfeedbackto design
Figure 5: Analysis ProcessThrough the process of requirements management, intimate understanding ofradio parameters, the system (RF cascade analysis) architecture andtest/measurement (model validation) shown above, we have specific knowledgeof the mechanisms that cause the destructive collaborative interference. Sometypical outputs of our studies are shown below.Freq (MHz)14.0IM Level 430Figure 6 Example Outputs: Broadband Nose, Passive InterMod andIntermodulation PlotsAfter Surveying and gathering data/characteristics of all platform/vehiclereceivers/transmitters, a cosite matrix is constructed. The layer 1 matrix includescombinations of radars, sensors and vehicles with communications payloads forplatforms/vehicles of interest. The layer 2 matrix is constructed for eachplatform/vehicle. The rows and columns include all emitters and receivers forboth communications and non-communications payloads. Rows representinterference sources and columns represent potential victims. Link priority isassigned to each link pair to determine the interference effects on overall systemperformance. The table below is a sample interference matrix for Intra-Platform.
ExampleNLOS- VehicleCannon#1JTRSxxx 1227/1575 MHz GPSAntenna1Acoustic SensorCombat Identification SystemxxxTransceiver (CEIU)Combat Identification SystemTransponder Antenna (TAS)Combat Identification System, VxxxxxxxxxxxxxxxDSID / RBCI Type II (ANT.-INTER.BCIS)111411111Med Range EO/IR Sensorexternal gimbal with lift/stow &Acoustic SensorCombat Identification SystemTransceiver (CEIU)JTRS 1227/1575 MHz GPSAntennaShort Range EO/IR Sensor onExternal gimbal with lift/stow &Multi-Function Radio Frequency(MFRF) System Antenna(w/armor)xxx 225-400MHz UHF DAMAJTRSAntenna21Cosite noise -90 dBm;Cosite noise -95 dBm;;System performance2 System performancedegredation due todegredation due to Cosite Cosite interference:interference: Comm range Comm range reducedreduced 25%; BER 1E-6 30%; BER 1E-6xxx 225-400MHz UHF DAMAJTRSAntennaMulti-Function Radio Frequency(MFRF) System Antenna(w/armor)xxx MBA VHF/UHF Antenna/LJTRSband AntennaItemComms ElementsJTRSxxx MBA VHF/UHF Antenna/Lband AntennaShort Range EO/IR Sensor onExternal gimbal with lift/stow &armorSensor ElementsExampleNLOS- VehicleCannonItemCombat Identification SystemTransponder Antenna (TAS)Combat Identification System, VDSID / RBCI Type II (ANT.Mine Detection Sensors Type I(Full provisions for payload primeSensor ElementsComms ElementsCosite noise -90 dBm;System performancedegredation due to Cositeinterference: Comm rangereduced 30%; BER 1E-6Cosite noise -98 dBm;1 System performancedegredation due to Cositeinterference: Comm rangereduced 30%; BER 1E-641111Mine Detection Sensors Type I (Fullprovisions for payload prime item)1Med Range EO/IR Sensor externalgimbal with lift/stow & armor1Cosite noise -98 dBm;System performancedegredation due toCosite interference:Comm range reduced30%; BER 1E-6Table 1 Sample Intra-Platform Interference Matrix(3) POST RECEPTION SIGNAL PROCESSINGJammerSignalHardware AppliquéLegacy ReceiverA/DDownConvertSPIR ModuleUpConvertD/A(a) HW Clip-on toLegacy Rcvr((((((SignalsJammerDominatesExisting ExistingAntenna AntennaAnalogRF-ICAnalogRF-ICSignals RF-ICSuppressesJammerSignals SPIRFurtherRemovesJammerDesiredSignalSoftware DefinedReceiverDownConvertA/DSPIR ModuleReceiverProcessing(b) SW Load toProgrammable RcvrFigure 7. SIPR module can be realized in older systems using a hardware appliqué andin new software-defined radios using software or firmware to achieve jammer
After the antenna and receiver front end overloading is addressed, digital signalprocessing (DSP) is used to further improve the robustness against the stronginterference signals. This Signal Processing based Interference Removal (SPIR)module leverages signal estimation and tracking algorithms, real-time subspaceinterference suppression, and Multiuser Detection (MUD) algorithms. The SPIRmodule provides accurate interference estimation, tracking and removal thatcannot be achieved with analog RF-IC techniques alone. At the front end of areceiver, the interference signal is overwhelming the desired signal (e.g. blueforce comms). The RF-IC module may cancel some of the interference to keepthe RF front end from saturating but the residual interference signal is stillstronger than the signal of interest. Next the signal is converted to digitalbaseband where the SPIR module, shown in Figure 8, estimates and tracks theremaining interference signals to digitally remove them from the desired signal.As shown in Figure 7 the SPIR module can be installed as either a hardware orsoftware appliqué to existing communications systems and SIGINT receiversenabling simultaneous operation during jamming. As a hardware appliqué, theSPIR module enables legacy radio or SIGINT systems to operate withoutmodification to their internal structure. As a software module, the SPIR moduleprovides software-defined systems with improved performance in the presence ofinterference through a software/firmware upgrade.In addition, Multiuser detectionA/D(MUD) are used for theinterferencewaveformJammer &suppression.MUDisaTo receiverJammer WaveformChannelRemovalProcessingtechnique used in digitalEstimationcommunications that breaksJammerJammerCoordinationStatefrom the traditional view thatChannelDecodingSPIR Moduleother users in the samebandwidth at the same timeFigure 8 Basic elements of the SPIR Module.should be treated as randomnoise (e.g. CDMA). MUD uses the fact that the other users are transmittinginformation bearing signals that have a defined structure. Using this model,receiver structures that simultaneously estimate and track the information signalsfrom all users can operate with much better throughput and lower probability oferror [1], [2], [3]. The adaptation of MUD for interference signals is quite naturalas modern, digitally generated interference signals are created from well-knownbuilding blocks, e.g. tones, chirps, pulses, etc. Communication signals areactually harder to remove because we don’t know the information that is beingsent. Interfering signals don’t necessarily encode unknown information in theirsignal, meaning that if we know the structure of the jamming signal then there istheoretically less impact on receiver. This can only be exploited if the receivertreats the interferer as a structured signal and NOT as noise. Today ALLstandard SIGINT and communications receivers treat jammers as unknownrandom noise. We propose to change this model.
To demonstrate how the interfering signal can be removed, we now show howone MUD algorithm, called successive interference cancellation (SIC) is used toreduce the impact of a stepped tone generator on a communication signal with ajammer to signal ratio (J/S) of 40 dB. For this simulation we create a digitalcommunication signal with a stepped tone generator that steps a quarter of theband every 10- s. Figure 9a a shows a spectrogram of the received signalbefore the interferer is removed. Using a current state of the art approach(tuning a bank of notch filters) to remove the interference is somewhatsuccessful, as you can see in 9b. However, the interferer is not completelyremoved and the filtering causes significant distortion to the communicationsignal because the impulse response of the filter required to create deep nulls isvery long which, in turn, creates very long inter-symbol interference for thecomms. This technique can be thought of as removing or nulling the signalsubspace where the interfering signal is strongest and using only the signalspace orthogonal to the interferer for comms (or sensing). This is effective forsome jam waveforms and at some power spreads between the jammer and thedesired signal but it does created unwanted distortion.In contrast, the SIC MUD algorithm makes a blind adaptive estimate for theinterfering signal and subtracts off the interferer estimate from the receivedsignal. We call this a blind estimate because the SIC is not informed about thefrequency or timing of the interferer. The result of using the SIC is shown inFigure c where the interferer is suppressed by over 40 dB without creatingsignificant distortion in the communication signal. The jammer signal is notcompletely suppressed when it switches between frequencies due to the blindnature of the estimator. Despite this, the jamming signal is removed during asignificant p
2010 NDIA GROUND VEHICLE SYSTEMS ENGINEERING AND TECHNOLOGY SYMPOSIUM . V. EHICLE . E. LECTRONICS & A. RCHITECTURE (VEA) M. INI-S. YMPOSIUM. A. UGUST . 17-19 D. EARBORN, M. ICHIGAN. Systems Approach to Ground Vehicle Electromagnetic Compatibility . Randolph Beltz – Sr. Principle Systems Engineer, BAE Systems . Dr. Bandon Hombs – Sr. Signal .
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