Characterization of the Ground-to-AirRanging Performance of the 960-1215 MHzARNS Band Using OFDM Measurements in

the 902-928 MHz ISM BandOkuary Osechas1, Nicolas Schneckenburger1, Wouter Pelgrum2, Elisabeth Nossek1, and Michael

Meurer1

1German Aerospace Center (DLR), Oberpfaffenhofen, Germany2Ohio University, Athens, OH

Abstract

In this paper we discuss the feasibility of prototypingradionavigation hardware, designed to operate in theARNS band, by flight testing it in the 902-928 MHzISM band. A central challenge in this effort wasthe shared nature of the ISM band, which causeshigh in-band interference levels and, consequently, areduction in the signal-to-noise ratio. We proposemitigating strategies that enable operation in theISM band, as well as a methodology for assessing theequivalence of results with ARNS band measurements.

Introduction

In the effort to provide Alternative Position, Naviga-tion, and Timing (APNT) systems, many future andexisting options involve signals in the AeronauticalRadio Navigation Service (ARNS) band. In order toobtain a valid, meaningful statistical model of anyAPNT system, it needs to be characterized with flightexperiments. However, regulatory constraints signifi-cantly hinder flight testing ARNS-band systems. Oneband adjacent to the ARNS band is the Industrial,Medical, and Scientific (ISM) band located between902 and 928 MHz. We propose that one possiblesolution to the conundrum of testing ARNS bandsystems is to resort to flight tests that use the ISMband.

As a test for the proposed solution we assess theperformance of a system based on OrthogonalFrequency-Division Multiplexing (OFDM) in the ISMband, using flight-test data gathered in the Summer of2015 at Ohio University. We compare the ISM band

data with data gathered from Distance MeasuringEquipment (DME) hardware in prior experiences[1, 2].

The procedure by which two data sets can becompared is depicted in figure 1. The comparison,which happens in terms of ranging performance,checks the consistency of the collected data withdata available from previous flight testing. We showhow the new data fits in with the older data ina way that supports claim that the two frequencybands are similar enough to each other to supportprototyping of ARNS band hardware in the ISM band.

This research was conducted under the hypothesisthat propagation in the ISM band is expected to bestatistically similar to the ARNS band, but momen-tarily different because of the differing signal phaserelationships. The time-varying nature of the channelis expected to lead to statistically equivalent channelproperties in both bands.

The equivalence of the two frequency bands, in termsof DME ranging errors, can be tested by checkingthe consistency of the performance prediction withinformation available from prior flight experiences [1].In checking the consistency between the two data setswe exploit the spatial information available for theDME ranging errors. The flight experiments weredesigned specifically to study gaps in the coverage ofexisting range error data. The spatial distribution ofpredicted ranging errors (from ISM band data) fits inwell with the existing data, as discussed in the resultssection.

Figure 1: Comparing the DME ranging performancein the ISM band with that of the ARNS band. TheOFDM signal, in the ISM band, is used to estimate thechannel impulse response at any given point in time.That channel impulse response is used to predict DMEranging performance and compare the result with theactually measured ranging performance of DME.

Methodology

Characterizing ranging in the ISM Band, as well asthe L Band, requires flight tests with hardware able tohandle both bands. The method is described in detailin [3], which discusses channel characterization ingreat depth. For the purposes of this paper, we takechannel characterization for granted and focus on theranging performance obtainable from predicted andmeasured DME errors, as transmitted in the ISM andARNS bands. A technical point to note is that theDME range measurements from the flight campaignin August 2015 were not yet available at the time ofwriting and the consistency of prediction with realitywas done by comparing behavior at a given locationwith the behavior at nearby, previously characterizedlocations.

Our setup uses a wide-band OFDM signal in the ISMband to characterize the air-to-ground radio channel.We use that information to predict the ranging errorcharacteristic for a DME signal (in the ARNS band).The resulting prediction is compared to the rangingerrors measured in previous flight experiments.

To make the results in the two frequency bandscomparable, we resort to assessing the rangingperformance, as an indicator of the potential ofthe radio channel to support navigation services.

Figure 2: The flight paths for both sorties, pictured inmagenta, were designed to facilitate the contrast be-tween areas with expectations of DME strong rangingerrors, with areas where DME errors were expected tobe milder. Each flight has one “dirty” and one “clean”radial portion, as well as transverse sections.

The ranging performance is computed from thechannel impulse response, by convolving the rangingwaveform (i.e. DME) with the channel impulse re-sponse and measuring the delay of the resulting signal.

The flight paths were partly designed to cover loca-tions previously not charted for DME ranging error.In addition each flight path was designed to have tworadial sections, where one was surrounded with areasknown to have high ranging errors (“dirty” radial)and the other was surrounded by points with muchsmaller errors (“clean” radial). For each flight, severalportions of orbitals were also included in the flightpath, with the expectation that the orbitals furtheraway from the base would have stronger errors thanthose closer to the base.

Hardware

The airborne set-up included all the hardware neces-sary to broadcast an OFDM signal in the ISM bandand a fully operational DME system. An arbitrarywaveform generator was configured to broadcast anOFDM signal optimized for channel characterization,as described in [3], which was amplified and broadcastthrough a dedicated L-band antenna.

The ground set-up was shared with a DME groundstation, which required diplexing the ISM-band signaland the ARNS-band signal. The two signals sharedthe antenna on the ground, which output it ISM bandsignal to a diplexer. The resulting ISM band signal

Figure 3: The ground side receives the OFDM signaland a DME interrogator signal; it also transmits DMEreplies through the same antenna. In addition, a GNSSantenna receives satellite signals that are used to com-pute an RTK-based ground truth, this enables precisesynchronization with the airborne system. DME re-sponse signals are generated using a USRP, also thedecoding of both DME and OFDM signals is done inthe USRP. The ground setup also generates virtualDME traffic, to simulate DME reception in a crowdedairspace.

went to a software-defined receiver, which sampeledthe incoming RF signal at 12.5 megasamples persecond.

In addition to the DME setup and the channelsounding hardware, both the aircraft and groundstation were equipped with a truth system, based onsatellite navigation hardware, to compute referencetrajectories and synchronize the clocks of both instal-lations. For details on the method, please refer to [3].

Signals

The setup requires signals in two different frequencybands: a standard DME signal in the ARNS bandand a channel sounding signal in the ISM band. Thechannel sounding signal has a much higher bandwidth

Figure 4: The airborne side produces DME interroga-tions and the OFDM channel sounding signal and re-ceives DME replies from the ground station. A GNSSreceiver distributes a 1 pulse per second synchroniza-tion signal to the on-board system, but it is also usedfor synchronization with the ground setup.

than the DME signal and, as such, the rangingperformance attainable by that signal itself does notmeaningfully compare with the ranging performanceof the DME signal. In this sense, the comparisonbetween two frequency bands needs a different figureof merit.

One option is to assess the ranging performance of thereal DME signal with the predicted performance of aDME signal, after the ISM band channel parametershave been estimated. A second potential approach isto correlate normalized ranging errors for both signalsagainst each other.

The DME signal consists of a Gaussian-shaped doublepulse envelope and is well described in [4]; for thepurposes of this paper it is only relevant that theDME signal is centered at 1107 MHz and has abandwidth of 0.5 MHz.

For channel sounding we use an OFDM-based sig-nal optimized for low peak-to-average power ratio(PAPR) [5] and uniform frequency spectrum, this

waveform is in accordance with the method of [6].For this set of experiments the channel soundingsignal was centered at 915 MHz, with a bandwidth of10 MHz. The autocorrelation functions of the base-band version of these two signals are shown in figure 5.

Figure 5: Comparison of the two signals. The autocor-relation (top) shows the finer time resolution achiev-able with the 10 MHz channel sounding signal, as theDME signal spreads over a much longer range. In thefrequency domain (bottom) the channel sounding sig-nal has a much more uniform distribution than theDME signal, in addition to a larger bandwidth.

An important feature of the two autocorrelationfunctions plotted in figure 5 is that the time res-olution of the OFDM signal is much higher thanthat of the DME signal; this is a consequence of thehigher bandwidth available for the OFDM signal.This higher time resolution is necessary to use thecomputed channel transfer functions as a means ofpredicting the DME ranging error.

In our setup, the OFDM signal is broadcast from theaircraft and received at the ground station. Since thewaveform is known and the time of transmission issynchronized between air and ground, using GNSS-based time stamping as described above, the receivedsignal can be deconvolved with the transmit signal toobtain an estimate of the channel transfer function orimpulse response.

Flight Path Design

From the data gathered from prior flight experiments[1] and from the visual inspection of panoramicimages taken from the location of the ground stationas presented in [2], we identified angular sectionsaround the ground station where strong rangingerrors are to be expected. Specifically, two sectors ofinterest go from 70 and 95 degrees and from 275 and355 degrees. These sectors correspond to areas where

Figure 6: The spatial correlation of ranging errorscan be described in terms of angular sections in whichstronger ranging errors are expected. From older testdata [1] this image simplifies the data of figure 2.Green lines indicate smaller measured ranging errors,red lines indicate stronger ranging errors. The areasindicated in gray are extrapolations of the prior data,where strong ranging errors are expected, given theerror scenario of figure 8. The traces in blue indicatethe flight paths that resulted from the considerationsderived from this fault model, each flight consisting oftwo radial sections, one going through the gray shadedareas and one avoiding those areas.

trees and other environmental features obstruct thehorizon [2].

Based on the occlusion model shown in figure 8we derive areas (or “slices”) in which high rangingerrors are expected, based on prior flight data. Infigure 6 we show a simplified version of the rangingperformance computed for figure 2 with smaller rang-ing errors indicated in green and stronger errors in red.

Figures 2 and 6 show the flight paths for the twosorties considered in this paper, one oriented towardsthe east of the ground station, the other towardsthe west. In both cases one radial aligns with anarea of strong errors (dirty radial), the other goingthrough an area of less errors (clean radial). Thedirty radial of the east-bound flight was set at 80degrees, which is inside the sector of ranging errorsbetween 70 and 95 degrees, a the clean radial was set

just to the north of that sector at 65 degrees. Forthe westward flight we chose a dirty radial at 300degrees, while the clean portion was set to 270 degrees.

The flight paths were designed in a way that the re-sults would unequivocally show whether the predictedDME errors resemble the measured DME errors ornot. Predicted errors along the flight paths should,therefore, exhibit a clean radial and a dirty radial, ifthey support hypothesis that testing in the ISM bandcan be used in the design of ARNS band hardware.

Predicting DME Errors

While it is possible to use the ISM band signal toprovide range measurements, the bandwidth of thesignal is so much higher than that of DME that theranging errors will be much smaller than those ofDME, simply because the signal has a much higherresolution in time than the DME signal would. Fora discussion of this observation, please refer to figure 5.

Predicting DME ranging errors, based on measuringthe received ISM band signal requires estimating theimpulse response of the radio channel. As indicatedin figure 1 the impulse response is computed by de-convolving an ideal DME waveform from the receivedISM band signal. The resulting impulse responseconsists of a set of complex weights that model theLoS and echoes that would be received at the groundstation, if the transmit signal were an ideal impulse.

Figure 7: The DME signal consists of two Gaussianpulses, modulated with a carrier at 1107 MHz (red).The received signal will typically contain a LoS compo-nent and one or more echoes (black). The time local-ization of a pulse is often defined as the point at whichthe pulse reaches half the maximum amplitude. Thegreen bars indicate the time transmission time and thereceive time that enables the range measurement.

The converse process can be applied to an ideal DMEsignal to determine what the receive waveform wouldbe, should the transmit signal in the ISM band beDME-like, instead of the OFDM signal. This canbe accomplished by summing delayed, attenuatedand frequency-shifted copies of an ideal DME signal,corresponding to the LoS signal and echoes identified

from the deconvolution.

By thus predicting the received waveform for ahypothetical DME transmission in the ISM band,we can then predict the ranging measurement thatwould obtained through such a channel. Knowing thewaveform makes it possible to apply a DME detectionalgorithm and predict the ranging error associatedwith the identified radio channel, as indicated infigure 7.

Comparing Predicted and MeasuredDME Errors

With the available data, one option for verifying thecomparability of ISM and ARNS band propagation isto exploit the spatial correlation of DME errors. Wepropose a model that allows assessing the plausibilityand consistence of the ranging predictions. We modelthe ranging error on the existing data as sections inazimuth and range, hereby distinguishing sectionswhere ranging errors are relatively strong from sec-tions where the ranging errors are relatively mild.

Modeling the error as angular slices is equivalentto attributing ranging errors to an occlusion orattenuation of the LoS, as suggested in [2]. For agiven altitude and azimuth angle an occluded LoSremains occluded if the user moves away from theranging source. The occlusion leads to an increasein the relative power of non-line-of-sight (NLOS)components compared to the LoS signal, which inturn can lead to ranging errors.

In scenario where the relative power of the NLOScomponents become sufficiently strong that the LoSpower is negligible by comparison, the measureddistance between transmitter and receiver is falsified.In that case the first signal to be detected at thereceiver is not the LoS (as it is occluded), but areflected signal, which by definition travels a longerdistance.

Any occlusion of the LoS that spans a finite range inazimuth angles leads to ranging errors that correlateover angular sectors, breaking up the area around theground station into “slices” (figure 8).

For the characterization of the ranging error around aterrestrial ranging source, the surrounding area maybe broken up into slices. Of these slices, some willhave stronger ranging errors than others, dependingon the availability of a LoS and on the multipathenvironment.

Figure 8: An aircraft flying along a path heading radi-ally away from the ground station, at a fixed altitude.If the line of sight to the ground station is lost, due toocclusion, it is unlikely to be recovered further awayfrom the ground station as the elevation angle becomessmaller.

Background Interference from Com-mercial Providers

The ISM band is open to unlicensed broadcasting,though some restrictions on power and modulationapply. In the planning phase of the flight trials,we expected non-negligible amounts of backgroundinterference. In field tests we did detect a strong back-ground signal in the lower portion of the ISM bandthat was attributed to a base station for a rural inter-net service provider (ISP). The ISP operates a groundstation located on a water tower, within eyesight ofthe OU airport, less than 2 km from our ground set-up.

The signal is pulsed in time, band limited, andrelatively high powered compared to the 1 W OFDMsignal broadcast by our setup. Figure 9 shows thetime-domain behavior of the pulsed signal over 3 ms,which includes 30 OFDM symbols. The top plot infigure 9 shows the pulsed nature of the interferencesignal, which has activity gaps in the order of 800 µsbetween bursts. In the frequency domain (bottomplot) we observe that the signal power concentrates inthe lower half of the band, leaving us to use 10 MHzin the upper half of the ISM band.

The strategy for leveraging the ISM band for experi-mentation, in spite of the strong background activity,was to yield to these heavy-duty users; we first yieldin frequency, by testing in the 915-925 MHz band,and then in time, by dropping measurements thatarrive during a burst of ISM band activity.

To make use of the ISM band signal we discard OFDMsymbols that are affected by interference and useonly those that are not affected. To detect degradedOFDM symbols we calculate the noise variance withineach OFDM symbol after correlation as described in

Figure 9: Time and frequency domain behavior of ISMband interference background. For this figure, we mea-sured the band from 905 - 925 MHz. The frequency-domain plot shows strong activity in the lower portionof the spectrum, which was attributed to an internetservice provider operating a base station 1.74 km awayfrom our ground setup, in Albany, OH. Zooming intothe upper half of the band, similar behavior can be ob-served, related to similar services located further awayand, therefore, received at a significantly lower powerlevel. The time-domain behavior shows the pulsed na-ture of the interferer. Depending on the time of theweek, the duty cycle of the pulsing could vary signif-icantly, from approximately 30% (most favorable ob-served) to approx. 80%.

[3]. OFDM symbols affected by exhibit a significantlyhigher noise variance as shown in figure 10.

Figure 10: The noise variance of OFDM symbols aftercorrelation indicates background interference. Sym-bols corrupted by interference are discarded for betterestimation of the radio channel.

Figure 10 shows the noise variance during a 250 mssegment. The figure is normalized to the variance ofthe white Gaussian background noise. We observe,

Figure 11: Filling in the predicted DME error at thelocations of the two test flights highlights the consis-tency of the predicted results with the known DMEranging errors.

that after correlation, time segments in which otherISM band users are active can easily be identified. Infigure 10 we can clearly identify one user transmittingvery short bursts with a repetition cycle of about200 Hz which are received at a power level of about16 dB relative to the white Gaussian noise power.Another interferer is transmitting with about 6 dBrelative power compared to the noise floor in a moresporadic pattern.

Results

The main result for this paper is that the predictedDME ranging error is consistent with observationsfrom older testing experiences. The predicted DMEranging errors are mapped onto the paths shown infigure 2 to generate figure 11.

For a better analysis of the consistency betweenprediction and observation we zoom into one of thetwo flights and show the detail in figure 12. In thecomparison we observe that the angular sectionswhere strong DME ranging errors are predicted aresurrounded by observations of strong DME rangingerrors. In particular, the dirty radial is locatedbetween two sections where strong ranging errorswere observed in the prior flights; furthermore, thedistance from the base at which ranging errors startbeing predicted along the dirty radial is also thedistance at which the ranging errors are observed for

Figure 12: Zooming into one portion of figure 11 helpsbetter appreciate the consistency between predictionand observation.

that angular section.

In addition, the clean radial runs through a portionof the plane where much smaller ranging errors werepreviously observed. The orbital portions of thepredicted error are also consistent with observation,as the strong predicted errors cut off exactly at thesame angles as the observed errors do at each orbitalsegment.

With regards to figure 12 it is important to notethat increased ranging errors can occur in cleanportions of the map that are not related to theterrain. A typical reason for such occurrences wouldbe the change in the relative orientation of theairborne antenna with respect to the ground, or anocclusion of the LoS by the wings of the aircraft.Further work is needed to adequately model this effect.

Discussion

An important overall goal on the road to providingintegrity from terrestrial ranging sources is under-standing multipath-induced ranging errors. Thesignal processing described above enables an in-depth analysis of the received signal, to such a level ofdetail that multiple propagation paths can be resolved.

From figure 12 we see that strong ranging errorsremain in locations where they were identified in priorflight experiments [1], which shows the importance

of characterizing the spatial correlation of rangingerrors. Furthermore, we note that large ranging errorstend to appear where the LoS is occluded and NLOSreception dominates the ranging measurement.

Since occlusion of the LoS is more likely at lowerelevations, this phenomenon explains why rangingerrors are worst at those points where the flight trackis furthest away from the ground station; since theaircraft maintained a constant altitude, the elevationangles at those far-away locations have the lowestelevation angles and, consequently, the strongestranging errors.

Considering that the results of the flight experimentshave so far been congruent with expectations, we seethe occlusion or attenuation of the LoS as a criticalcomponent of ranging errors from terrestrial sources.Occlusions of the LoS are a consequence of geomet-ric relationships, such as the position of the aircraft,position of the ground station, and position of obsta-cles; as such, the frequency dependence of occlusionsis negligible, compared to the frequency dependence ofother ranging error mechanisms. Therefore, we expectthe ranging errors for hardware operated in the ISMband to approximate ranging errors for hardware inthe ARNS band enough to support prototyping activ-ities.

Future WorkA topic of great interest is the influence of airframeorientation on ranging errors. In satellite navigation,ranging errors are typically assumed to be a functionof the satellite elevation angle at the aircraft position;recent developments suggest that more accuratemodels could be computed, if relative elevation andazimuth angles are included in the model [7]. Ina similar fashion, it appears logical to account forthe relative orientation between aircraft and groundstation, as occlusions of the LoS can be caused byparts of the aircraft and the alignment of the antennapattern with the LoS can also cause a disturbance ofthe direct signal.

Another potential line of work is the study of differentquantities that correlate well over space and influencethe ranging error. It may, for example, be feasible tomap scatterers or to compute visibility masks in thevicinity of terrestrial ranging sources. Conversely, adual problem would be to derive siting criteria withthese methods. A map of incidences of ranging er-rors would certainly be a useful tool in assessing theavailability impact of a particular terrestrial rangingsource.

SummaryAssessing the ranging performance of radionavigationsystems is essential in providing reliable positioningservices. Licensing issues make it cumbersome torun flight experiments with uncertified hardware thatuses the ARNS band at 960-1215 MHz. Instead, thiswork shows that it is possible to test hardware in thenearby ISM band at 902-928 MHz with comparableresults. This finding enables a new approach todeveloping avionics systems, as it simplifies theprototyping and characterization stage. In particular,the new approach is an appealing prospect for thestudy of multipath-related ranging errors in terrestrialradionavigation systems, as the physical setup couldpotentially be used for experiments anywhere in ITURegion 2 without requiring any licensing.

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