Beasley, Piers

Ritchie, Matthew

English

UCL Discovery

bladeRAD: Development of an Active and Passive,Multistatic Enabled, Radar SystemPiers J. Beasley1, Matthew A. Ritchie2Department of Electronic and Electrical Engineering, University College London, UK{1piers.beasley.19, 2m.ritchie}@ucl.ac.ukAbstract — In this paper the development of a hybrid activeand passive experimental radar system utilising a low-costSoftware Defined Radio is explored. The potential futureevolution from monostatic to multistatic sensing is describedand the synchronisation performance limitations of the systemare summarised through a number of preliminary laboratoryexperiments. In addition, the first of a series of practical radarexperiments are presented in order to verify the systems activeand passive sensing modes.Keywords — Multistatic Radar, Software Defined Radio,FMCW Radar, Software Defined Radar, Passive Radar.I. INTRODUCTIONThe topic of hybrid active passive radar is gaining moreattention with a number of papers starting to surface on theexpected benefits from the hybrid architecture [1], [2], [3].A hybrid system can capitalise on the strengths of passiveradar (PR) (e.g. zero transmitter cost, covert operation), aswell as the strengths of active radar (e.g. optimised waveform,transmit beam-steering). However, little is published onthe design of such a system, and therefore few empiricalresults have been reported to concretely support the claimedperformance enhancements. Until now, the complexity andcost of implementing a hybrid system will likely have beena limiting factor. With the recent advancements of SoftwareDefined Radio (SDR) technology, SDRs now provide low-costhighly flexible platforms that can be used to perform themultiple functions at multiple frequency bands required of ahybrid radar system.As the capability and accessibility of SDRs has increased,research into the exploitation of SDRs in radar applicationshas become more prevalent. One particular SDR, the UniversalSoftware Radio Peripheral (USRP), is used in a large quantityof the published work on SDR radar. A good example of theuse of the USRP in a PR system can be found in [4], [5], whereresearchers from the University of Cape Town develop an FMPR system to successfully detect aircraft flying into CapetownInternational Airport. Additionally, an example of an activesystem, developed around a USRP NI2920, can be found in [6],where an Frequency Modulated Continuous Wave (FMCW)system was verified for a limited set of short range experimentsdetecting static targets at ranges up to 12m. As the technologycontinues to mature, more SDRs of comparable performanceto the USRP are becoming available, but for a fraction of thecost e.g. bladeRF xA4, LimeSDR and RTL-SDR.This paper presents the development of an experimentalhybrid active passive radar system utilising one of theselow-cost high-performance SDRs. The architecture of thehybrid system is introduced before, presenting empirical resultsfor transmitter (TX) to receiver (RX) synchronisation. Insection III the future evolution from the monostatic system,described section II, to a multistatic system is briefly explained.Section IV reviews some preliminary active and passive results.In the final section, a conclusion of the work is presented alongwith a plan for future work.II. SDR BASED ACTIVE PASSIVE RADAR SYSTEMThe Nuand bladeRF micro 2.0 xA4 is a low-cost highlyversatile SDR available to purchase for approximately 480USD. A cross comparison between with a selection ofcomparably priced SDRs found the bladeRF xA4 to be mostsuitable for the purpose of multi-functional multi-frequencyradar applications. Of considerable interest, is the bladeRF’shigh central RF limit of 6GHz, surpassing the LimeSDR,XTRX CS, bladeRF x40 and KerberosSDR. The bladeRF xA4hosts the AD9361 transceiver RFIC, capable of 2 X 2 MIMOoperation with channel bandwidths dynamically selectivebetween 0.2MHz to 56 MHz, making the SDR particularlysuitable for hybrid radar applications. An evaluation of thebladeRF xA4’s predecessor, the bladeRF x40, for use inStepped Frequency Continuous Wave (SFCW) Radar can befound in [7], [8]. Though the x40 uses a different LMS6002DRFIC. A more recent publication [9], assesses the use of anxA4 SDR as an SFCW radar for breast screening exams, wherea detailed evaluation of the xA4’s TX and RX performanceover its entire RF range can be found. The focus of this paperis to evaluate the architecture of a hybrid radar system, andpresent some initial experimental results using the developedsolution.1) bladeRF CLIIn this work, the vendor supplied bladeRF Command LineInterface (CLI) running on a host PC was used to administercontrol to the SDR through the USB 3.0 interface. The CLIallows access to the majority of the SDR’s functionalityincluding, importantly, the ability to synchronously streamTX and RX channels between the SDR and PC. Thisis fundamental for radar signal processing. When usingthe bladeRF CLI to simultaneously stream TX and RXchannels, the bandwidth of the USB 3.0 interface was foundto considerably limit the maximum cumulative bandwidthsachievable with the four SDR channels (there is a widelyunderstood full-duplex bandwidth limit of 40 MSPS betweenSDR and PC [9]).A. Monostatic Radar TransceiverWhen developing an active radar transceiver usingthe bladeRF, considerable buffering issues resulting frombandwidth constraints of the USB 3.0 interface were avoidedby splitting the TX and RX streams across two separate SDRs.In this configuration a 40MHz transceiver bandwidth wasverified, by connecting both the TX SDR and RX SDRs to thesame Dell XPS laptop running Ubuntu. Given this bandwidth,B, the attainable transceiver range resolution, ∆R, can becalculated to be 3.75m, using equation (1). Where v is thespeed of light in Earth’s atmosphere.∆R =v2B(1)1) Signal ProcessingDue to the waveform versatility of the SDR, the transceiveris capable of both FMCW and Pulse-Doppler radar sensing.In both radar modes all radar signal processing is donepost capture in MATLAB®. When using the radar in FMCWmode, unlike conventional hardware defined FMCW radars,deramping of the receive channel is done post capture in DSPusing a prerecorded FMCW chirp, see Fig.1.Fig. 1. Simplified signal processing flow of bladeRF based monostatic FMCWradar transceiver.2) Transmitter and Receiver SDR SynchronisationThe bladeRF xA4 has the external control inputs andinternal circuitry required to synchronise TX and RX eventsacross multiple bladeRF SDRs. The start of acquisitions canbe synchronously triggered by sharing a trigger signal from theTX SDR to RX SDR, see Fig. 2. Additionally, the TX SDRcan also share its 38.4MHz Voltage Controlled TemperatureCompensated Crystal Oscillator (VCTCXO) with the RX SDRin order to synchronise the DACs, ADCs and data clocks acrossthe two boards. In this configuration the RX SDR uses the TXSDR’s VCTCXO signal in the place of its own, see Fig.2. Thisfunctionality, allows multiple SDRs to be used in parallel withthe equivalent baseband performance to a single device.3) Radar Trigger AccuracyTrigger error will only impact the start of the TX/RXacquisition, though will result in a constant target rangeestimation error for the continuation of the capture. Anexperiment was conducted to test the trigger accuracy of thetransceiver. This was done by transmitting a single pulse fromthe TX port to the RX port via a 40m RF cable. The 40mRF cable was used in order to delay the pulse, simulating astationary target at a know fixed range. The results from 200trigger experiments are presented in Fig. 3. It was found thatthe trigger performance resulted in zero range error for 62%of triggers, and a ±1 range bin error for 37.5% of triggers.This error results from the method in which the triggers aresetup on the FPGA using the bladeRF CLI.Fig. 2. bladeRF based monostatic FMCW radar transceiver. Comprising oftwo bladerRF xA4 SDRs, one acting as TX and the other RX. Acquisitionsynchronisation achieved through sharing of a trigger signal from TX SDR’sFPGA to RX SDR’s FPGA. Baseband sampling synchronisation achievedthrough sharing of 38.4MHz VCTCXO from TX SDR to RX SDR.Fig. 3. Stationary target range bin errors resulting from radar triggerinaccuracy between TX and RX streams. Results gathered for 200 triggerevents in FMCW mode.4) Monostatic Radar Phase MeasurementSelf-loop tests using a 40m section of RF cable wereperformed to verify the transceivers phase stability in theDoppler domain through long recordings. Though basebandoperations are synchronised across multiple SDRs, the bladeRFdoes not contain the internal circuitry required for phasecoherent RF operations. That said, both TX and RX RFPLLs, used for pass-band mixers, are derived from a commonVCTCXO. Therefore, we should expect the RFs to be coherent,yet exhibit a random constant relative phase offset. The phasestability of a 2.4GHz central frequency was evaluated over a120s period by connecting TX and RX port via a 40m RFcable in order to simulate a stationary target at a known fixedrange. After identifying the range bin containing the pseudotarget, the phase series was attained by taking the argumentof the complex samples down the slow-time dimension of theradar matrix. The phase series was then unwrapped to remove2π discontinuities. Fig.4 illustrates the phase series for twoidentical 120s experiments. The results from both experimentswere first normalised to zero, before the second experimentsphase series was then offset by 0.1 radians. In the first 15s ofboth captures an initial phase excursion, of in the most extremecase 0.12 radians, can be observed. The cause of this excursionis not yet fully understood. However, for the continuation ofthe capture a net phase drift of < 0.05 radians (2.87 Hz) isobserved in both results. Indicating an RF synchronisationerror of < 79.6 × 10−6Hz, resulting in a negligible targetDoppler velocity error. The coherent integration loss resultingfrom the phase noise can be calculated from the phase seriesvariance using Richards’ analytic expression [10]. The worstcase variance was found to be 4.30×10−4 radians, resulting inan inconsequential coherent integration loss of 8.04×10−7dB.Fig. 4. 2 Minute 5kHz PRF monostatic radar phase series of pseudo stationarytarget for two identical 2.4GHz experiments. TX and RX channels connectedvia 40m RF cable.B. Passive Radar ReceiverThe bladeRF’s two receive channels make it suitable foruse as a PR receiver: one for sampling the direct path from aIO, and the other for sampling IO reflections from targets.In addition, the frequency agility of the receive channelsalso make it suitable for use with a variety of Illuminatorsof Opportunity (IO). Though, the results presented in thispaper are limited to using a 2.4GHz Wi-Fi IO. The activetransceiver in section II-A can be developed into a hybridsystem through the simple addition of a third SDR for purelypassive sensing. In this work, the reference and surveillancechannels are processed in MATLAB® using a batched PRprocessing algorithm as described by Bo Tan et al in [11].III. MULTISTATIC RADAR SYSTEMThe hybrid radar system evaluated in the previous sectioncan be further developed into a multistatic system throughdisciplining multiple radar nodes to a common externaltrigger and frequency reference. The bladeRF SDR featuresa secondary method for clock synchronisation of multipleboards, by utilising the on-board ADF4002 PLL to disciplineits VCTCXO to an external frequency reference. This featureallows common frequency reference sources such as GPSDOsto be used to synchronise spatially separated SDRs. A GPSDOradar synchronisation system has been developed in parallelwith the work described in this paper. The purpose ofthis system is to provide synchronous trigger and frequencyreferences to spatially separated radar nodes, removing therequirement for physical synchronisation cables. The finalpaper submission will include: further details on the methodfor time and frequency distribution; bladeRAD’s multistaticperformance limitations.IV. ACTIVE PASSIVE RADAR EXPERIMENTSIn this section, a series of active and PR results arepresented from experiments using the multi-functional radarsystem introduced in Section II. The experiments wereconducted in a small laboratory environment, illustrated inFig.5, using either a human or micro-drone as a radar target.For the active experiments the system was setup inFMCW mode with a central frequency of 2.45GHz using themonostatic transceiver configuration detailed in II-A. Thoughthe bladeRF is capable of a 8dBm CW ouput power at 1GHz,the max output power at 2.45GHz is 0dBm. A saw-toothwaveform with a bandwidth of 40MHz and PRF of 5kHz wasselected. Both TX and RX channels were connected to 18dBiparabolic dish antennas via 2.4GHz ISM pass-band filters. ForPR experiments, an Archer C9 Wi-Fi Access Point (AP) wasused as an IO. A 20MHz 802.11n Wi-Fi channel, centred onon a 2.437GHz, with a power of 20dBm was configured. TheWi-Fi channel was stimulated using the MGEN network trafficgenerator tool [12]. 18dBi parabolic dish antennas were againused for both reference and surveillance channels.Fig. 5. Experimental setup for active and passive laboratory experiments.Antenna locations and orientations for active FMCW radar experiments andWi-Fi based PR experiments are indicated by red filled antennas and bluefilled antennas respectively.1) Human TargetThe first results presented are of a human walking directlyback and forth from the radar. Vertical antenna polarisationwere selected for both radar modes. Following the necessaryradar signal processing, a single delay line Moving TargetIndicator (MTI) was implemented in the active radar data todiscriminate the moving target from the considerable stationaryclutter. Fig. 6. details the spectrogram results for the active andpassive radar captures. The Doppler shift contribution fromthe radial movement of the human’s torso can be observedat ±20 Hz in both FMCW and PR results. In the activeresult, the periodic streaks of Doppler centered around thebulk Doppler are associated to the free swinging movementsof the human’s limbs. These periodic streaks represent thecharacteristic micro-Doppler signature of a human’s gait [13].(a) (b)Fig. 6. Spectrogram results for human target walking back and forth fromactive and passive radar. Spectrogram window duration of 0.2s, with 90%overlap and zero padding factor of 4. (a) result for S-Band FMCW Radar; (b)result for Wi-Fi PR capture2) Micro-Drone TargetThe next result presented is for a DJI Spark micro-droneflying slowly back and forth from the radar. In this experimenthorizontal polarisation of antennas was selected. Additionally,in order to overcome the considerable interference introducedby the micro-drones 2.4GHz radio control system, a poweramplifier was introduced in to the FMCW radars TX chain,increasing the TX power to 19dBm. The Spectrogram resultfor the active experiment is detailed in Fig. 7. Helicopter RotorModulation (HERM) lines can be observed with a spacing of±400Hz around the micro-drone’s bulk Doppler. HERM linesresult from the micro-motion of the micro-drone’s propellersand exhibit a frequency spacing equal to the number ofblades per propeller, multiplied by the propeller rotational rate[14]. In the final paper submission, direct signal interferencecancellation will be operated on the passive radar results tobetter expose both targets’ micro-Doppler signatures; a passiveresult will then also be included for the micro-drone.V. CONCLUSIONIn this paper, the ’bladeRAD’ hybrid radar systemdeveloped with a combination of synchronised low-costbladeRF xA4 SDRs is presented. In section II the TX to RXSDR synchronisation is evaluated, and the RF phase erroris found to result in negligible Doppler offsets at a 2.4GHzRF. The impact of triggering errors between SDRs is alsopresented, where the error is limited to ±1 range bin for99.5% of acquisitions. However, it is thought this error couldbe rectified in post processing using the back-scatter from astationery clutter reference at a known fixed range. Section IVreports some preliminary results for active and passive sensingof both a human and micro-drone, though the results arelimited to frequency domain analysis, due to the limited radialmotion of the target in relation to the radar’s range resolution.Future work will focus on the development of bladeRAD intoa multistatic system, at which point further experiments will beconducted for larger target ranges and a variety of multistaticscenarios.Fig. 7. Spectrogram result for micro-drone target flying back and forthfrom S-Band FMCW Radar. Spectrogram window duration of 0.2s, with 90%overlap and no zero padding.REFERENCES[1] F. Wang and H. Li, “Joint waveform and receiver design forco-channel hybrid active-passive sensing with timing uncertainty,” IEEETransactions on Signal Processing, vol. 68, pp. 466–477, 2020.[2] H. Kuschel, J. Heckenbach, and J. Schell, “Deployable multibandpassive/active radar for air defense (dmpar),” IEEE Aerospace andElectronic Systems Magazine, vol. 28, no. 9, pp. 37–45, 2013.[3] Y. Gao, H. Li, and B. Himed, “Joint transmit and receive beamformingfor hybrid active-passive radar,” IEEE Signal Processing Letters, vol. 24,no. 6, pp. 779–783, 2017.[4] S. Heunis, Y. Paichard, and M. Inggs, “Passive radar using asoftware-defined radio platform and opensource software tools,” in 2011IEEE RadarCon (RADAR), May 2011, pp. 879–884.[5] C. Tong, M. Inggs, and G. Lange, “Processing design of a networkedpassive coherent location system.” IEEE, 2011, pp. 692–697.[6] S. Costanzo, F. Spadafora, A. Borgia, H. O. Moreno, A. Costanzo, andG. Di Massa, “High resolution software defined radar system for targetdetection,” Journal of electrical and computer engineering, vol. 2013,pp. 1–7, 2013.[7] J. Marimuthu, K. S. Bialkowski, and A. M. Abbosh, “Stepped frequencycontinuous wave software defined radar for medical imaging,” in2014 IEEE Antennas and Propagation Society International Symposium(APSURSI), July 2014, pp. 1909–1910.[8] K. Takahashi and T. Miwa, “Near-range sfcw uwb radar based onlow-cost software defined radio,” in 2019 IEEE Radar Conference(RadarConf), April 2019, pp. 1–6.[9] D. Carvalho, A. J. Aragão, A. Ferrari, B. Sanches, and W. Noije,“Software-defined radio assessment for microwave imaging breast cancerdetection,” in 2020 IEEE Nordic Circuits and Systems Conference(NorCAS), Oct 2020, pp. 1–6.[10] M. Richards, “Coherent integration loss due to white gaussian phasenoise,” IEEE signal processing letters, vol. 10, no. 7, pp. 208–210, 2003.[11] B. Tan, K. Woodbridge, and K. Chetty, “A real-time high resolutionpassive wifi doppler-radar and its applications,” 2014.[12] R. B. Adamson, MGEN-3.0 User’s Guide, U.S.Naval Research Laboratory, 2021. [Online]. Available:http://www-hera-b.desy.de/subgroup/network/mgen/UserGuide.html[13] F. Fioranelli, M. Ritchie, and H. Griffiths, “Analysis of polarimetricmultistatic human micro-doppler classification of armed/unarmedpersonnel,” 2015.[14] P. Beasley, M. Ritchie, H. Griffiths, W. Miceli, M. Inggs, S. Lewis, andB. Kahn, “Multistatic radar measurements of uavs at x-band and l-band,”in 2020 IEEE Radar Conference (RadarConf20), Sep. 2020, pp. 1–6.

bladeRAD: Development of an Active and Passive, Multistatic Enabled, Radar System

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bladeRAD: Development of an Active and Passive, Multistatic Enabled, Radar System

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