RadioScience, Volume32,Number6, Pages 2345-2358, November-December 1997
The Manastash Ridge radar' A passive bistatic for upper atmospheric radio science
radar
John D. Sahr
Department of Electrical Engineering, University ofWashingtrot, Seattle Frank D. Lind
Geophysics Program,Universityof Washington, Seattle Abstract. We describea novel method for radar ren•ote sensingof the upper atmosphere which reliesupon commercialFM broadcastsnear 100 MHz. Thesebroadca,sts have high
average powerandexcellent radarambiguity function.With properpro•essing wecanstudy the spatial and temporaldistributionand Dopplerspectrumwith excellentand completely unambiguous resolution.Sincethis passivesystemhas no transmitter,there are enormous benefitsin safety, expense,shielding,antenna and receiverdesign,and licensingissues. Some new problemsare introduced, but these are solvedwith relatively little expense. After presentingthe technicalbasisfor sucha radar• we describean instrumentthat we are buildingat the Universityof Washingtonto studyhigh-latitudeplasnxairregularitiesin the E region. 1. Introduction
For decades,ground-basedincoherentand coherent scatter radars have been superb tools for the
Kofman, 1991]. Both methodscollectall possible range-lagproductsbut cancelthe unwanted(clutter) terms; alternating codesaccomplishthis deter-
ministically, while random codesfunction stochastically. Usingthe ambiguityfunction [Levanon,1988] study of turbulence and plasma parametersin the as a guide, one achievesthe initially startling but Earth's ionosphere.Theseradars operatein frequencorrect understanding that random signals are very ciesfrom 10 to 1200 MHz, sometimesrequiring high power. The target is almost always "overspread," good radar waveforms. Noiselike transmitter waveforms have other usewhich means that the range extent times the Doppler ful features: They have potentially high duty cycle; bandwidth exceedsthe speed of light. For such tarthey can mitigate systematic flaws in receiver sysgets one cannot unambiguouslyestimate the power tems; and they may be available for free. As we spectrum using periodic pulses and Fourier transwill demonstrate, commercial FM broadcasts near forms. Nevertheless,by taking advantageof the stochastic 100 MHz provide a very high quality source of illumination for a variety of atmosphericand iononature of the target one can unambiguouslyestimate spherictargets. These transmissionshave constant the range dependentautocorrelationfunction [Farley, 1969; Brekke,1977]. For many yearsthe stan- amplitude and are derivedfrom musicand speechsignals. Yet their (stochastic)ambiguityis superb.We dard tool was some variant of the "multipulse" techare currently building a passive rada• at the Uninique (still widely used). In the last decadea new classof high duty cycle codeshas becomeavailable: versity of Washington, and we will describeits dethe "alternating codes" [Lehtinen and HiiggstrSm, sign and expected performance below. We expect 1987]and randomcodes[Sulzer,1986;Haglotsand to achieve range resolution of about i km without sufferingrange or velocity alias. Having decidedto build sucha radar, we find that Copyright1997 by the AmericanGeophysical Union. a number of benefits accrue. Since we do not build
or operate a high-powertransmitter, the costsavings are very large. Furthermore,without a transmitte•
Paper number 97RS-02454.
0048-6604 / 97/ 97RS-02454511.00 2345
2346
SAHR AND LIND: PASSIVE BISTATIC RADAR FOR.ATMOSPHERIC RESEARCH
we eliminate licensingand substantialsafety issues. Electricpowerconsumptiondecreases markedly.Receivernoisefigure is improvedbecausepreampsmay be connected at the antenna terminals, eliminating lossesassociated with long transmissionlines and transmit/receiveswitches.The antennasmay be designedfor high gain without needingto accomodate high (transmit) power. Of course,there are penalties. A sensitiveradar must be bistatic, which complicatesthe logisticsof acquiring,storing,and transportingthe data. The underlyingsignal processingalgorithm is straightforward but computationally burdensome.However, the tremendous advancesin digital technologyare rapidly mitigating these difficulties. Some limitations are more subtle.
Since the transmitter
is al-
and Inan et al. [1996]have made numerousobservations of VLF
beacons to infer bottomside
iono-
sphericstructure,and in the last decadepreciseobservationsof total electroncontent(TEC) between satellites and ground stations have permitted tomographicreconstructionof large-scaleionospheric structure. Our approachresemblesa "true" radar in that rangeand Dopplercharacteristics are computed directly from the scatteredand transmitted waves. One might argue that a passiveradar is not a true radar since we do not control the transmitter.
How-
ever, modern high-performance,high-powerradar systemssamplethe transmittedsignalto correctforflaws developedafter the ideal waveform generation passesthrough the imperfectmodulators,drooping power supplies,etc. In a sense,these radars don't
wayson, the dynamicrangeof the processed data is control the transmitter, either. clutter-limited over the entire range; for reasonable 1.2. Geophysical Objectives operatingparametersthe clutter floor is about 40 dB We were motivated
beneath the strongest scatterer.
to build
a coherent
scatter
Followinga brief descriptionof other radio experiments which passivelyobserveother transmitters, we will give an overviewof our geophysicalobjectives. A major sectionwill focus on the algorithm at the heart of the technique, followed by a description of
radar in order to study ionosphericirregularities in the auroral E region. Theseirregularitiesarisefrom density gradient and electron streaming instabilities which generateion soundwave turbulence,with characteristic Doppler velocities up to about 2000
our new radar.
m/s. The quiescentionosphereis effectivelytransparent at frequenciesaboveabout 30 MHz, but when
1.1. Other Examples of Passive Radar
the electron density is roughenedby ion acousticir-
The idea of passively observing radio broadcasts for geophysicalinformationthrough scatteringis not new, and examples can be found at the beginning of radio technology.Marconi had transatlantic communications in mind in 1901, but the existence of the radio link implied the existenceof an ionosphere.
regularitiesthere is strongscatteringthroughoutthe
scatter of HF radio waves from a heated portion of the ionosphere, making clever use of the inner
soundingrocket observations,but there are many details of electrojet turbulencewhich are poorly understood. These details include saturation amplitudes,
VHF spectrum. Given the large scattering crosssection, relatively small radars are capable of detecting the radio scatter of this phenomenon. Many investigatorshave studied this phenomenon;
for an originaltheoreticalwork seeFarley [1963],or The (Radio) Luxembourgeffect revealedmutable more recentreviewsby $ahr and Fejer [1996],Halstructureof the ionosphere[Tellegen,1933]; satel- doupis[1989],Fejer andKelley [1980],andFejer anti lite beaconscintillations(Sputnik series,late 1950s) Providakes[1987]. Experimentally,theseirregulariand whistler waves[Storey,1953]revealthe distant ties are found to attain very large amplitudes. ht very generalterms, there is a suitablenonlinearthestructure of the plasmasphere. More recently,Beley et al. [1995]usedturbulent ory which explains the gross features of radar and
"quiet" portion of conventionalAM broadcasts(no sidebandenergybetween+25 Hz). Howland [1994] linear and nonlinear stability thresholds and direchas used television
broadcasts
to track
aircraft
at
tions, and even suchfundamental issuesas the proper
100-kmranges,and Griffithset al. [1992]havealso numericaldefinitionof the ion acousticspeed[Kisexperimentedwith Direct BroadcastSatellite (DBS) sacket al., 1995]. There is evidence that the scattering process is broadcasts(althoughwith lesssuccess).One would wavelength dependent,and an examinationof the expect substantialclassifiedresearchin this area. at 50 and 140 MHz shows There is no simple distinction between "passive Dopplerspectraobserved in spectralshape.However,it radar" and "beacon"studies. Gummet et al. [1996] importantdifferences
SAHR AND LIND: PASSIVE BISTATIC
RADAR FOR, ATMOSPHERIC
RESEARCH
2347
is difficult to state this conclusively,becauseof the profound differencesin the experimentsat 50 and 140
lation. A zero mean audiosignals(t) modulatesthe
MHz [$ahr and Fejer, 1996]. Thus, it is desirableto make detailed measurementsnot stronglyaffectedby
follows:
frequency of a radio wave of mean frequency f0 as
the experimental apparatus or techniques,especially at an intermediate frequency. A few measurements
x(t) - cos 2•rfot+ •
s(t•)dt•
(1)
have been made at 90 MHz [Uspensky,1985]; we wished to improve and extend the information avail-
The parameter a adjusts the bandwidth of x(t),
able in this important wavelengthregime, with particular emphasison long-term measurementsrather than short-term, "event-driven" incidents. There are other practical issues as well. While 50 MHz offerslower bandwidths and signalprocessing advantages,50 MHz is occasionallysusceptibleto ionosphericrefraction, which complicatesinterpreta-
which is about 300 kHz for commercial
index of refraction approachesthe vacuum value as the inverse square of the operating frequency,there is significantlylessrefraction at 100 MHz than at 50
ples samples of an FM broadcast are plotted in the
broadcasts,
and the stations are assigned800-kHz channels(in Seattle). A power spectrumof a real broadcastestimated from a 1-s sampleis illustrated in Figure 1. Fromequation(1) we immediatelyseethat the transmitted waveform has constant magnitude and that the modulation is nonlinear. The constant magnition of (vertical) interferometry.Sincethe effective tude is illustrated in Figure 2, in which 5000 sam-
MHz.
So our goal is to make new, detailed, long-terns observations of auroral electrojet turbulence. We also expect routine observationof meteor trails, aircraft, and perhaps large satellites. We demand that the data be straightforwardto analyze through the absenceof range and Doppler aliasing and that it provide usefulpower spectra and eventually interferomtery at a relatively unexaminedwavelength. Additionally, we desirethat the radar be inexpensiveto build and operate. This instrument is also intended to be a vehiclefor training studentsin radar remote
inphase/quadratureplane. The nonlinearitymakes the broadcastbandwidth significantlylargerthan the bandwidthof the signals(t). Given the largelyaperiodic nature of speech and music, FM broadcasts
are completelyaperiodicand decorrelate(in an average sense)in just a few microseconds.The short correlation time is responsiblefor the excellent radar
application of FM broadcasts. The ambiguity function estimated from a 1-s sample of a commercial FM broadcast is shown in Figure 3. Toward the end of this paper we will describe the
radar we are building, its expected sensitivity, and logisticsissues.In the next sectionwe spend considerable time developingthe data analysisproblem and
sensing.
PowerSpectral Den•ty of 100.7MHz FM, 1 second of data,2 048averages 0
1.3. A Description Commercial
!
of FM Broadcasts
FM broadcast
stations transmit
wave-
forms encoded with stereo audio signals. These broadcastsare found from 88 to 108 MHz; the transmitter power is typically about 30 kW. This is comparable to the peak power of instruments such as the ScandinavianTwin Auroral Radar Experiment
(STARE) and the CornellUniversityPortableRadar Interferometer(CUPRI). However,FM broadcasts havea 100%duty cycle,and sothe averagepoweris quite large in comparisonwith auroral instruments.
The FM transmitting antennapattern is typically m• omnidirectionaldisk illuminating the horizon,with a gain of about 6 dB. We will not dwell on the details of the stereo mod-
-lO
-15
-30
-35
-45
_5• - 50
I
-2OO
I
-150
i
-100
ß-50i
i
0
•10
i
100
i
150
i
200
250
frequencydeviationfrom 100.7MFIz FM (KHz)
Figure 1. Estimate of the power spectrum of a com-
ulation scheme[seeZiemer and Tranter,1990].The mercial FM broadcast at 100.7 MHz, from 1 s of data., basicidea canbe illustratedwith monophonicmodu- _ which was sampledon our radar receivers.
2348
SAHR AND LIND: PASSIVE BISTATIC RADAR FOR ATMOSPHERIC use of random
waveforms
RESEARCH in radar
studies
of over-
spread targets. Much of their work is immediately applicable to this problem. The developmentbelow is quite general, and the expressionsand formula are applicable to any radar
0.0015
0.001
waveform. 0.0005
This
fact is obscured
when the trans-
mitter signalis known (or assumed)in conventional radar applications, and the sparsenessof low duty cycle transmitter waveforms permits computational optimizations which are unavailablefor high duty cy-
0
-0.0005
cle waveforms.
2.1. The Scattered
-0.001
Signal
If we denotethe signalbroadcastby the transmitter x(t), then the signalarrivingat a receivery(t) is a
-0.0015
linear combination of delayed and modulated trans-
-0.002
-0.002 -0.0015 -0.001 -0.0005
mitter waveformsx(t),
Figure 2. A scatterplotof 5000 samplesof a comx(t ta,(2) mercialFM broadcastat 100.7MHz. When plotted in the inphase/quadrature plane,the sampleslie on a circleindicatingthe constantmagnitudeof the FM where a(t,r) is the target scatteringamplitude at broadcast.Deviationfromthe circleis dueprimarily time t and range cr and cr is understood to include to noiseand multipath propagation. the r -n power scalingfactor associatedwith scatter from the targets at differentranges(2 > %. with such software, the task is not simple because a Let us first examine the scattering cross-section certain amount of knowledgeof the target correlation functions must be encoded into the process. contribution to the integrand. The full expressionfor the variance is presented in the appendix, but the most significant contribution of these terms will vanish in the same limit
as the
6(p"- q") + {aaaa) - Re,r)R*(•, r),(p'-q')
is as follows:
self
,A) -•-,A 5(q'-q" )(20) R(-• R*( q' ) 5(p'-p") cross
A = Because
t'-t"
each term
(21) contains
two Dirac
delta
dr t
func-
(26)
tions, the integralswill simplifyby 2 orders,although in different parts. These two contributionshave been indentified as the "self" and "cross" components, as they distinguish between the self-noisevariance and the cross-noise
The
variance.
calculation
of the variance
is made difficult
w•• •, •- • • (•^½•(•/2)•'(•/2, o)+•,•') (27) Here P is mean squared power of all scatterers,
TACF is the correlationtime of the target,andT• is
by the combinatoricblossomingof the integrand. No 'the maximum range extent in time units. singleterm is particularly difficult, but keepingtrack Although not strictly necessary,we offer the folof all 48 requires some care. Furthermore, numerous
(reasonable)approximationsare necessaryif the resuiting expressionsare to be written in a compact and understandable form. Fortunately, the approximations all have the effect of increasingthe magnitude of the result, so that the expression presented below is actually an upper bound on the variance. At any rate, we need to compute
Wr(0) =
lowingdefinitions for Tr andTACF:
TACF(r/2 ) _R2•(r/2, 1 0)fo •IR.(r/2,•)I•d• (28) T•= f•f•(r/2)IRa(r/2, 0)1 •'a• (20) I%(r/2,0)1 •'a• IRa(r/2, O)j2 dr p2_•1f0øø
(30)
We can conveniently write the uncertainty in ml sel f+cross (23)estimate normalized by the zero lag,
2352
SAHR AND LIND: PASSIVE BISTATIC
+
T• P2
TACF R• (r/2,0)
RADAR FOR ATMOSPHERIC
(31)
If we are attempting to measurethe power at a certain range, such that the power at that range
RESEARCH
A strongerclutter suppression tool is available, however.The target •(r/2,t) evolveson timescales muchlongerthan the transmitterwaveform,sothere is opportunity for somecoherentintegration,which will be definedpreciselyin the next section. Coherent integrationalsohas strongimplicationsfor the tractability of this algorithm. For the moment we simply observethat the dynamic range is improved linearly with coherent integration:
R(r/2, 0) is comparable to the typicalpowerP, and for targetswhoserangeextent Tr is lessthan the
AQ_
IV 1+
Q-
correlation timeofthetargetTACF (anunderspread
rx
Tr
Tcoh TACFR•(r/2,0)
target), we find that
AQ Q .• • •TAc TF In other words, the uncertainty is inverselyproportional to the number of independent samplesof the
Of course,the coherentintegrationinterval must not exceedthe inverse of the anticipated target bandwidth.
Referringagainto Figure 3, we seethat the range resolution is approximately 2 km. If coarser range resolution is acceptable, then incoherent averaging
targetTACF/T. Indeed,onecandonobetterthan of lag products in the range direction can further this evenin the absenceof clutter (whichis possible improve the dynamic range. for .underspread targets). For the ionospheric irregularities that we intend to study, with an integration time T • 10 s and anticipated target correlationtime
TACF • 30ms,theexperiment yieldsanuncertainty of about 5% of the zero lag power. In estimating the uncertainty above, it was assumed that the power in the range of interest was comparableto the typical target power and that the target was underspread. We hope to study overspread targets with significant dynamic range and
4. Estimator
Implementation
Issues
At this point we have shownthat the passiveradar scatter can be manipulated to yield the target correlation as a function of range. Expressedin discrete time, the operation is
Q[r/2, •-]- • y[t]x*[t-r]y*[t-•-]x[t-r-•-] (34)
must therefore work to minimize the effects of clut-
t
ter arisingin the second factorof equation(31).
= Z yx[t; r]yx*[t - •-;r]
There are two possibilitieswhich permit enhanced
(35)
t
dynamicrange through clutter suppression.The first possibilityis describedby Hagj•orsandKo•man For a reasonable implementation at 100 MHz, we [1991]whonotethat the lagresolution is muchfiner should sample the receivers 500,000 times per second; we shouldcomputethe scatter out to 1200 km than the typic• timesc•e of the correlation•nction. Thus one can averagetogether many adjacent (8 ms, or 0 < r < 4000) and lags out to 250 ms lag estimatesto reducethe statisticalfluctuations (0 • •- • 125,000). Thereforethe total computaassociatedwith the clutter. For example, the correlation time of the FM waveformis about 10 •s, while the correlation time of the target is certainly greater
tional burden for the "brute force" implementation
is B - 500,000x 4000x 125,000= 250x 10x2oper-
ationsper second.Evidently,this signalprocessing than i ms, sowe can averageNinc = 100 adjacent cannot be performed in real time; a 1-GFlop computer couldhandle I s of data per day. fine lag estimatesto modi• the uncert•nty: Fortunately, the brute force calculationcan be tremendouslysped up by taking advantageof dec-
AQ
TACFI d
Q -_• T
FT•P R•(r/2, • Ninc 1TAC • 0)(32)
imation and Fourier transform implementations of
correlations. First, we create the "detected"signal yx[t;r]: So, for our target this incoherentaveragingincreases yx[t;r] = y[t]x*It - r] (36) the sign• to clutterratio (SCR) by about 10 dB.
SAHR AND
LIND:
PASSIVE
BISTATIC
RADAR
FOR ATMOSPHERIC
RESEA[?•CH
2353
Now the Q[r/2, r] is the autocorrelationof yx[t;r],
more than three decimal digits of precision would arise simply by averaging so many measurements. Since this is significantly more precisethan the selfnoise fluctuations, there is no real advantage in using a multibit digitizer. One-bit digitization dramatyx[t;r] is a noisyestimateof the scatteringampli- ically simplifies the data acquisition, data storage, tude a(r/2, t), which variesmuchmore slowlythan and transport and speedsthe initial stagesof signal the transmittersignalx[t]. Thus the detectedsig- processing. nal may be decimated,or coherentlyaveraged,by a and using Fourier transform methods to evaluate the correlation, the computational burden is reduced to about 40 GFiops, a large but feasibleamount. Further optimization is possibleby observingthat
substantial
4.3. Real Signals with Simulated
factor: N-1
YX[ta; r] -- Z yx[ta + t;r]
(37)
t=0
For our purposes, N m 100, so the decimation step vastly decreasesthe subsequentflow of data through the signalprocessorand stronglyreducesthe clutter power. In fact, the decimation step so limits the subsequentdata flow through the processorthat the decimation step dominates the computation. There is nothing magical about the decimation. If the data had been analyzed in the Fourier domain, the "decimation"would have beenautomaticallyapplied. Ultimately, the combination of decimation anti Fourier correlation reduce the computational burden by 5 orders of magnitude to about 2 GFlops for full real-time operation. With further refinements in the processingalgorithm and the ever increasingpower of inexpensivecomputers, we expect to be able to
Targets
To test the algorithm, we have recorded real FM broadcastsand numerically scattered them from simulated targets. In Figure 4 we showan examplewith three targets, expressedin the range-Dopplerplane. The three targets are narrow sinusoldsseparatedby about 2 km, with different Doppler shifts and different amplitudes. Even with only 1 s of data, all three targets are easily resolved. Note that the clutter is confinedto the vicinity of the strongestscatterer, a
...J•l._•kl•l•d, œ•.,L ..... 1-•6&?&•C:7& TT [lt'lF'l, il I.. ___œ ....... 1 bUl•d. J.l•l•t-k] 11i:[b ljHdl-lU!'lll•d[l
V•IoV U.•DII/•UI•
more extensive simulations, additionally demonstrat-
ing that if the data are truncated to sign bit only, there is no discernibledifferencein the quality of the subsequentrange-Doppler calculations.
5. Description Ridge Radar
of the Manastash
We now describethe basic designof the Manastash
support continuous real-time operation within a few
Ridge Radar (MRR). A sensitiveradar must some-
years.
how prevent the transmitter signal from directly entering the receivers. In most radars this isolation is performed in the time domain, by enabling reception during a substantial period when the transmitter is
4.1. Interferometry If two antennas are available to collect the scat-
tered signal,producingy,(t) and y,•(t), the appropriate cross correlation which contains phase difference is
silent.
In the case of our new radar
the isolation
is
performed spatially, by physically displacingthe receiver from the transInitter by about 100 km, past an intervening mountain range. Of course, performing the signal processingrequiresknowledgeof the transmitted signal, so a secondreceiveris located near the transmitter simply to record the actual broadcast.
r,r)- IY,•X(r r)YmX*(r;r)! (38) At somepoint we intend to include an interferometric capability in our radar. 4.2. Coarse Quantization
For the experiments we will run, the typical un-
certaintyin lag product will be about 5% of the zero lag, and 10- or 20- secondaverageswill result from the compilation of severalmillion samples. If we were to sample the receiversbut retain only the sign bit.
Thus this radar is fundamentallybistatic (tristatic if you includethe transmitter). The referencereceiver(x(t)) will be locatedat the Universityof Washington(UW) campusin Seattle, and the weak signalreceiver(y(t)) will be located at the University of Washington Manastash Ridge
Observatory (MRO), operated by the Physicsand Astronomy department at the University of Washington. The Observatory has superb location at an
2354
SAHR AND LIND: PASSIVE BISTATIC
RADAR FOR ATMOSPHERIC
RESEARCH
AmbiguityFunctionof 100.7MHz FM withSimulated Targets AmbiguityFunction •f 100.7MHz FM withSimulated Targets 0.9
0.,5
:.::. :...::-.•:. 0.4 0.2
'• o.• 'i:':--::':•.... 0.2 1000
0.1
500 0 -500
-lOft)
r•ns½ 0an)
0 -1500
-500
v½lochy
0
500
1000
• clocity (m/s)
Figure 4. Three simulated targets detected in 1 s of data. The transnfitter waveform is from actual samplesobtained from one of our receivers;the targets are synthetically added.
On the left is a meshplot (linear amplitude),and the right figureis identical,with contours and shadingindicating the presenceof scatterers. elevationof 1060 m and a clearline of sightto Central
WashingtonUniversity(CWU) in Ellensburg,Washington. A fast microwavelink betweenMRO and the CWU Geology department permits full Internet capability at MRO, supporting data transfers of 500 kbits/s. The Internet link is important for transporting the data, operating the radar remotely (accessis difficult duringwinter), and will enableuseof the radar for instructional purposesat the UW and elsewhere.
5.1. Sensitivity
Analysis
Before proceedingtoo far it is useful to consider whether the systemhas sufficientsensitivityfor radar performance. Our intended target is the ion sound wave turbulence found at the base of the aurora, and
we will compareour radar's parametersto that of the CUP RI systemusing the radar equation [Levanon,
1988], Pt--
PTGTGR,h2 er (47r)3R4
performanceis suggestedin Table 1. This is a very conservative comparison; among other things, the MRR receivercan have smallerbandwidth. The very strongestsignalsexperiencedby CUPRI have signalto-noise ration (SNR) exceeding30 dB, so there is ample sensitivity available. 5.2. Receiver
Design
Our receivershave particularly simple direct conversiontopology. After some coarsepreselectionmt Table
1.
Monostatic
A Comparison of the Performance of and Bistatic
radars
CUPRI
MRR
Parameter sensitivity, dB PT 50 kW +47 Duty cycle 0.02 -17
sensitivity, dB 30 kW +45 1.0 0
GT GR )•2
4.0 14.0 9.0 m2
Totals
25.0 25.0 36.0 m:•
+14 +14 +16 +74
+6 +14 +10 +75
wherePT,R are the transmittedand receivedpow- A very modestreceiveantennais assumedand ideners, GT,R are the transmitter and receiverantenna tical receiverperformance,with the result that the gains, R is the slant range, and er is the scattering crosssection. Assumingthe samescattering volume, slant range, and receiverbandwidth, a comparisonof
two radars have similar sensitivity. Abbreviations are CUPRI, Cornell University Portable Radar Interferometer, and MRR, Manastash Ridge Radar.
SAHR
AND
LIND:
PASSIVE
BISTATIC
RADAR
RF gain stage is followedby a single inphase and quadrature(IQ) mixer with localoscillatorsetto the centerfrequencyof the selectedradio station. The IQ mixer is ibllowed by low-passfiltering and additional gain, at which point the IQ signalsare sampled. Ordinarily, direct conversionreceiversare not used becauseof potential self-interferencefrom the transmitter
and its exciters
and because of ease of estab-
lishing selectivity and low noiseat a fixed intermedi-
ate frequency(IF). However,whenthere is no transmitter near the weak signal receiver,the first of the concernsis void. The modulating waveformhas the property that zero Doppler information will not be concentrated at zero frequency of the IQ baseband signal, so any dc offsetsin the receiversare easily eliminated.
In a sense,the receiver is dual conversion;the first local oscillator is sinusuoidal, but the secondis not
(the referencesignalx(t) has constantmodulusbut is accomplishednumerically. With those features in mind the single conversionreceiver is very simple, and we avoid subtleties of high-order interference arising from multiple conversiontopologies. 5.3. Time and Frequency Synchronization
Becausewe wish to accuratelyestimate the target range, the two receiversmust be time synchronous. The fundamentalrangeresolutionis about i km, or 6 •us,sothe time uncertainty betweenthe two receivers should be rather smaller. This problem is solved by two Global PositioningSystem (GPS) receivers, each of which providesa one-pulse-per-second signal. The mutual jitter of these signalsis lessthan 100 ns, which is adequate for range resolutionof 15 m. We wish to measure Doppler velocities accurate
FOR ATMOSPHERIC
RESEARCH
2355
Antenna
T University of Washington Receiver •Direct Conversion I VlDigitizer I Receiver
]
Q
I
1MHz Reference I •
Internet
I I Conne GPS Stabilized ]1HzTrigger .
Crystal Oscillator I
Centralized I
Signal Processing I
Hardware I Antenna
T Manastash Ridge Receiver I
I
•Direct Conversion I i!Digitizer Receiver
I
Q
I
I 1MHzReference I '
i GPSStabilized ll HzTrigger
Crystal Oscillator I Figure 5. A block diagram of the system. The two receiversexchange data via a true, fast internet connection. The sampling and mixing synchronization is provided by Global Positioning System receivers. tape drivescapableof supportingthis data flow, that is avcry undcsirablc solution. Wc do not intcnd to record raw data for anything other than brief tests or specialevents. Instead, we will immediately trans-
port the data for real-time processing. It is either difficult or expensive to continuously
transport4 Mbits/s overa distanceof 100km. However, it is possible to significantly reduce the data
to i m/s, corresponding to 0.67 Hz at 100 MHz, so rate. As mentioned above it is acceptable to record the radar receiversmust agreeto 0.67 Hz (although only the sign bit of the data, reducing the raw data. they neednot agreewith the transmitter). The GPS rate to 500 kbits/s. There are two principlemethreceiversalsoprovidea superbfrequencyreferenceof 1.0 MHz +10 •uHz. A block diagram of the pair of receiversis shownin Figure 5.
ods for further reducing the data flow to our design target of 100 kbits/s. The simplest method is to operate the radar with
a duty cycle of 15%, recordingdata for 10 min per 5.4. Data Transport, Storage, and Quantizahour. A variation of this plan would involve contintion uous operation but only transporting data in which The receiversare designed to produce250,000(IQ) signal was apparent. This has the advantage that samplesper second,and the two receivers'signals meteor echoescould be used to provide upper atmomust be brought to a single location for processing. sphericwinds as a by-product of regular operation. Alternatively, we could compressthe data. AlWith 8-bit sampleswe would needto store 1.8 Gbytes per hour, or 45. Gbytes per day. Although there are though the sign bit data stream will have very high
2356
SAHR AND LIND: PASSIVE BISTATIC
RADAR FOR ATMOSPHERIC
RESEAI{CH
entropy and thus cannot be compressedwithout loss, it can be compressedif we are willing to tolerate increased quantization noise. The technique is beyond the scope of this report, but we have successfully compressedthe raw data by a factor of 30 in a way
compared with the transmitter waveform correlation
that permits recoveryof unbiased(but noisy)power
the infinite
spectra. That compressionmethod will be the topic of a future report.
relationwaspresent.This (upperbound)permitted
function R(r). 2. Integrals involving the time averagewere computed over the finite interval T if the integrand had no dependenceon the transmitter waveform or over interval
if the transmitter
waveform
cor-
us to avoid vastly more complicated expressionsin-
volvingthe error functioneft(z). 6.
Conclusion
We have describeda means to make high-quality radar measurementsof ionosphericturbulence by relying upon commercial FM broadcasts. The peculiar structure of the wideband frequencymodulation achievesremarkably good resolution of range and Doppler shift, eliminating range and Doppler ambiguities that complicate data interpretation. We have shown that the signal processingproblem is tractable and have showninitial observationsusing the receiverswe have developedto verify the analysis. We expect the first observationsof irregularities by the end of 1997. The underlying method is quite potent. There is sufficientsensitivity to detect meteors,aircraft, and perhapseven somesatellites. By lookingon oblique forward paths it should be possibleto detect scatter from tropospheric and stratosphericlayers. Because
3. Integrals involving the range axis were computed for all positive ranges if the integrand did not depend upon the transmitter waveform or over the infinite interval if it did. Again, this provides an upper bound and avoidscumbersomeexpressionsinvolving the error function. 4. A number of the integrals in the time average are best computedwith a changeof variablesleading
to a weightingfunction W(t), which is the triangular unit hat function centered at t = 0. Although this function was retained during the calculations, it is droppedbelow becauseintegraridsare only significant for times Itl > r•, the appearance of factors of/• indicates extremely strong suppressionof what would other-wise be enormous clutter terms. In fact, we will present the total clutter organizedby the exponent possible to do better if many stations are simultaneof/•, namely ously recorded, since their waveformswill doubtless be independent. Var(Q)= •ø½o+•½•+•½• +•½•+•2½•2 (•o)
Appendix: the
A Complete Expression for
Variance
By taking advantage of a computer algebra tool we have been able to generate a reasonablycomplete expressionfor the variance of the estimator. In order to evaluate the various integrals we have chosento make a number of important approximations.
1. Target correlationfunctionsR•(r, r) are always assumedto be slowly varying in both r and r,
Clearly, not M1 powers of • are present. Earlier, we have shown approximately half of C0, and we show the complete expressionsnow.
-
l•m (•)2 (
+
+
+4
+
SAHR
AND
......
LIND:
PASSIVE
BISTATIC
RADAR
FOR ATMOSPHERIC
+
+
RESEARCH
2 ,r' + R r 2 • "
+2,5
-
I - k2'
I
]1
,r ,
2357
+
+
r•]oR•(r +r'' r)R•(r - r'' r)dr'+
2T
IR•((r - r)/2, 0)l 2)+2•lR(r/2, r)
(41) I • IR(r/2 0)l 2 •T '
(45)
Earlier we listedonly the termsproportion•to rJ
in anticipation that they were fundament•ly larger
In truth, one would have to dig deeply into these
than thoseinvolvingr•. Noticethat the rJ terms expressionsto extract much meaning. We offer the
include integr•s over •1 rangesor lags. The rest of the clutter terms should be negligible if one avoidslooking at sm•l correlationlags. It might be argued that we have chosenan unre•istically strong decorrelationin the Gaussianmodel; however,we m•ntain that this an•ysis at least identifies the nature of the clutter, consistentwith the hypothesis that the correlation time of the transmitter waveform
is much shorter
than
the correlation
time of the target.
following three m•n observations: 1. There
are some correlated
the range and lag differ kom the desiredrange and lag. None of these correlationssurvive in the dominant part of Co. 2. The correlated errors are, in general,lesssevere for targets at large rangesobservedat long lags. 3. Some of the clutter terms do not decrease with
integration time T and are only insignificant to the o•,o• •h• •t• • n p,,• differently •ho•o• • •_ imum use•l ingegraCion time which dependsupon ul•ima•e decorrelationof •he •ransmig•erwaveform;we do no• expec• ghis •o be a limigafion of our system. A differen•
,•
+
errors in which both
model for •he transmitter
correlation
function would develop a different clutter expression,perhapsvasfiy different. Nevertheless,•he basic propergyof clu•er suppression •hroughdecorrelation of the •ransmiCCer waveformwill rem•n ghesignifi-
,-
can• factor.
-
R•
r
Acknowledgments. The authorsare gratefulfor
x
support from the National ScienceFoundation Divi-
sionof AtmosphericSciences(grant ATM 93-57864)
R• 6 ,r' dr'+ • T
R(r'r)dr'x (43)
with matching support from Intel Corporation; front
the Air Force Office of ScientificResearch(gran[ 046159); and from URSI. References
C6
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