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Advances in Space Research xxx (2010) xxx–xxx

Advanced architectures for real-time Delay-Doppler MapGNSS-reflectometers: The GPS reflectometer instrument

for PAU (griPAU)

E. Valencia *, A. Camps, J.F. Marchan-Hernandez, X. Bosch-Lluis, N. Rodriguez-Alvarez,I. Ramos-Perez

Remote Sensing Lab, Dept. Teoria del Senyal i Comunicacions, Universitat Politecnica de Catalunya and IEEC-CRAE/UPC, Campus Nord,

Building D3, Jordi Girona 1-3, 08034 Barcelona, Spain

Received 16 October 2009; received in revised form 1 February 2010; accepted 1 February 2010

Abstract

In recent years Global Navigation Satellite System’s signals Reflectometry (GNSS-R) has stood as a potential powerful remote sens-ing technique to derive scientifically relevant geophysical parameters such as ocean altimetry, sea state or soil moisture. This has broughtout the need of designing and implementing appropriate receivers in order to track and process this kind of signals in real-time to avoidthe storage of huge volumes of raw data. This paper presents the architecture and performance of the Global Positioning System (GPS)Reflectometer Instrument for PAU (griPAU), a real-time high resolution Delay-Doppler Map reflectometer, operating at the GPS L1frequency with the C/A codes. The griPAU instrument computes 24 � 32 complex points DDMs with configurable resolution(DfDmin = 20 Hz, Dsmin = 0.05 chips) and selectable coherent (minimum = 1 ms, maximum = 100 ms for correlation loss Dq < 90%)and incoherent integration times (minimum of one coherent integration period and maximum not limited but typically <1 s). A highsensitivity (DDM peak relative error = 0.9% and DDM volume relative error = 0.03% @ Ti = 1 s) and stability (Dq/Dt = �1 s�1) havebeen achieved by means of advanced digital design techniques.� 2010 COSPAR. Published by Elsevier Ltd. All rights reserved.

Keywords: GNSS-R; GPS; Delay-Doppler Map; Sea-state; Digital design

1. Introduction

Global Navigation Satellite Systems (GNSS) signalshave been world-widely used for navigation and position-ing purposes. These signals are transmitted by satellite con-stellations and provide global coverage. Although manysystems are available or will be in the near future such asGLONASS, COMPASS, GALILEO, etc. it is the GlobalPositioning System (GPS) the one that has the widestacceptance, and it is fully deployed and operational.

However, this kind of signals can be used for other pur-poses than just positioning or navigation and specifically,

0273-1177/$36.00 � 2010 COSPAR. Published by Elsevier Ltd. All rights rese

doi:10.1016/j.asr.2010.02.002

* Corresponding author. Tel.: +34 934054664.E-mail address: [email protected] (E. Valencia).

Please cite this article in press as: Valencia, E., et al. Advanced architecturreflectometer instrument for PAU (griPAU). J. Adv. Space Res. (2010), d

they can be used as opportunity signals to remotely sensegeophysical parameters after being scattered over theEarth’s surface. This technique is called GNSS Reflectom-etry (GNSS-R) and was first introduced for mesoscalealtimetry by Martın-Neira, (1993) who proposed to processthe received signal, after reflecting over the surface underobservation, by correlating it with local replicas of theGPS code generated with different time delays. The resultof this technique is a function called waveform that relatesto the scattered power as a function of the time delay. Dif-ferent approaches of this technique have been proposed fora number of remote sensing applications, especially toderive ocean altimetry and sea state (Zavorotny and Vor-onovich, 2000; Cardellach, 2001; Rius et al., 2002; March-an-Hernandez et al., 2008b).

rved.

es for real-time Delay-Doppler Map GNSS-reflectometers: The GPSoi:10.1016/j.asr.2010.02.002

http://dx.doi.org/10.1016/j.asr.2010.02.002

mailto:[email protected]


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The determination of the sea state is a key issue for SeaSurface Salinity (SSS) retrievals using L-band microwaveradiometry (Font et al., 2004), and may be the limiting fac-tor in the final achievable accuracy. In order to improve thequality of SSS retrievals, the PAU instrument was pro-posed in 2003 to the European Science Foundation (Campset al., 2004a, 2009). This project consists of the develop-ment of a suite of three instruments: a digital beam-form-ing pseudo-correlation radiometer; a GPS reflectometersharing the same RF front-end, IF back-end and analog-to-digital converter; and an infrared radiometer.

In the framework of the PAU project, the basic GNSS-R observable to work with has been chosen to be the wholeDelay-Doppler Map (DDM), since it captures the asymme-tries of the DDM tails due to the relative motion betweenthe GPS transmitter and receiver, as well as for the relativedirection of the wind speed and the instrument lookingdirection. The DDM tails asymmetry can be importantfor spaceborne receivers, as shown in Fig. 1 for two differ-ent scenarios: 12 m/s wind speed and receiver’s velocityvector parallel and perpendicular to the scattering plane.The DDM is obtained by correlating the received signalwith local replicas of the pseudo-random noise (PRN) codeshifted in time, and also in Doppler frequency with respectto the delay and Doppler frequency at the specular reflec-tion point. It is a 2D function that is related to the scatteredpower distribution over the surface. As it takes intoaccount all the power contributions of the complete glisten-ing zone (i.e. surface zone that contributes to the receivedscattered power) it contains more information (i.e. azi-muthal dependence) than just the peak value, or the time-domain waveform.

Moreover, the normalized DDM volume has beenproposed as an efficient direct sea roughness descriptorthat can be directly linked to the brightness temperaturevariations due to the sea-state effect (Marchan-hernandezet al., 2008c; Valencia et al., 2009). To assess the theory,

Fig. 1. Simulated DDM �3 dB contour plots for a LEO (h = 700 km) GNSS-R(left) receiver’s velocity vector parallel to the scattering plane and, (right) rece


two field experiments have been undertaken in the Can-ary Islands (Marchan-Hernandez et al., 2008b; Valenciaet al., 2009) with very encouraging results.

In this paper, the GPS Reflectometer Instrument forPAU (griPAU) design, implementation and performanceare presented. The griPAU instrument is a real-time GPSreflectometer that computes high resolution complexDDMs coherently integrated during 1 ms, the duration ofthe GPS C/A code at L1 (1575.42 MHz). These basic1 ms DDMs can be averaged coherent (amplitude andphase) or incoherently (amplitude-only).

The griPAU instrument has been developed from a pre-vious operational version (Marchan-Hernandez et al.,2008a). This former version has been redesigned applyingstate-of-the-art digital design techniques so as to improveand enhance the instrument’s performance by achieving ahigh synchronism and taking the most benefit of the avail-able hardware resources in the Field Programmable GateArray (FPGA). The main elements of the system that havebeen replaced or modified are listed in Table 1 along withthe resulting system improvements.

2. Instrument description

2.1. Principle of operation

The purpose of the griPAU instrument is to compute theDDMs in real-time by correlating the received scatteredsignal s(t) with a local replica of the GPS C/A code a(t)for several values of the delay (s) and Doppler offsets (fD):

DDMðs; fDÞ ¼Z T c

0

sðtÞaðt þ sÞexpð�j2pðfL1 þ fDÞtÞdt;

ð1Þwhere (s, fD) are the delay and Doppler coordinates, and Tc

is the coherent integration time. The noise-free received di-rect signal s(t) has the form:

receiver in two different spaceborne scenarios for a wind speed of 12 m/s:iver’s velocity vector perpendicular to the scattering plane.



Table 1Main system modifications and their resulting improvements/enhancements.

Former instrument version griPAU Improvement/enhancement

Software control unit Dedicated hardware finite states machine (FSM) control unit High synchronism level achieved and improvedstability and sensitivityInput data buffer based on two RAM

memories sharing a busInput data buffer based on a dual-port RAM memory using asingle bus

– Single and ultra-stable clock referenceDelay estimation algorithm only used

I component of the direct signalDelay estimation algorithm enhanced to use both in-phase (I)and quadrature (Q) components of the direct signal

Improved robustness in front of multi-path andsignal fading

Linear polarisation antenna for thedirect signal path

Right hand circular polarisation (RHCP) antenna for thesignal path

– Revised synchronism of the delay estimation algorithm Reduced delay estimation time from 16 to 5 ms– Revised and optimized resource usage DDM size increased from 16 � 16 to 24 � 32

pointsFix antenna for the reflected signal

pathAutomatic tracking of the specular point over the scatteringsurface

Scatterometric measurements not affected bythe antenna radiation pattern modulation

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sðtÞ ¼ffiffiffiffiffiffiffiffiffiffiffiffi2P C=A

pDðtÞaðtÞcosð2pðfL1 þ f 0DÞtÞ

þffiffiffiffiffiffiffiffi2P P

pDðtÞP ðtÞsinð2pðfL1 þ f 0DÞtÞ; ð2Þ

where D(t) is the navigation message, P(t) is the preciseGPS code, PC/A is the transmitted power of the in-phasecomponent, PP is the power of the quadrature component,and f 0D is the Doppler shift induced by the relative motionof the transmitter and the receiver. In GPS positioning andnavigation receivers the navigation message is decoded. InGNSS-R receivers this is not usually the case as it is the gri-PAU case, so changes in the navigation bit cause p-radphase jumps that will drastically reduce the resultingSNR. Unless phase jumps are compensated for, this effectwill limit the maximum coherent integration time to20 ms at most, which is the period of the navigation bit.

As it can be seen in Eq. (2), the received signal under-goes a Doppler shift f 0D as it propagates from the transmit-ter to the scattering surface and then to the receiver. Tocorrectly track the reflected signal the system has to be ableto detect and correct this Doppler shift. As griPAU hasbeen designed to work mainly for ground-based applica-tions at low heights, the Doppler shift induced in thereflected signal is the same as the induced in the directone, and depends only on the transmitter motion. How-ever, for airborne or spaceborne operations, the actualDoppler shifts would have to be computed from geometricconsiderations using the navigation solution derived by theuplooking GPS receiver:

fD ¼V t�! � bni � V r

�! � bns

k; ð3Þ

where fD is the Doppler frequency shift related to the specu-lar reflection point, V t

�!is the transmitter velocity vector, V r

�!is the receiver velocity vector, bni is the incidence directionunitary vector, bns is the scattering direction unitary vector,and k is the electromagnetic wavelength. Considering themaximum relative radial velocity among a ground fixedpoint and an orbiting GPS space vehicle, the minimum rangeof Doppler frequencies that the receiver has to be able tocompensate for is –5 kHz < fD < 5 kHz (Tsui, 2000).


The implemented griPAU signal processor is embeddedin a Xilinx Virtex 4 FPGA device using the VHDL hard-ware description language. The size of the computedDDM is limited by the available hardware resources. Thisimplies that the Doppler shift of the received signal, as wellas the time delay of its code have to be a-priori known so asto center the computing window around the DDM peak.The total number of correlators that can be implementedwith the available resources not only determines the finalDDM size, but also its resolution, as it will be discussedin detail in Section 2.3.

The implemented architecture has a total of three signalpaths: one chain for the reflected signal and two for thedirect signal to estimate the Doppler shift and time delay.A Trimble GPS receiver is used to obtain the Doppler shiftof the direct signal, as well as other geometry parameterssuch as the elevation an azimuth of the satellite to betracked. However, the estimated time delay from the com-mercial GPS is not precise enough, and it is not updatedfrequently enough to keep track of the reflected signal.The time delay is then estimated from the direct signal bymeans of a circular cross-correlation algorithm, Eq. (4),implemented in the signal processor.

RsD;a ¼ IFFT ðFFT ðsDÞ � FFT �ðaÞÞ; ð4Þ

where sD is the direct signal down-converted to basebandand with the Doppler shift corrected. Using a circularcross-correlation based algorithm has the main advantagethat it works in a continuous single acquisition state sono extra time is needed prior to start tracking the signal’sdelay. This allows the estimator to get locked very fastand quickly recovers if it gets unlocked. Other approaches,such as the early-prompt-late correlation algorithm (Tsui,2000) require an acquisition state prior to tracking whichcan last too much for the presented application. Neverthe-less, these other approaches demand more hardware re-sources to implement the required control logic.

Once the time delay and Doppler shift of the direct sig-nal are known, these parameters are used to center the




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DDM window in the (s, fD) domain. Then, according tothe DDM size and resolution, the (s, fD) coordinates arespecified in samples and Hz. The coordinates of each binare used to generate a set of signals which are local replicasof the baseband C/A code with the corresponding timedelays and Doppler shifts. These signals are correlated withthe down-converted reflected signal so as to obtain theresulting DDM (Marchan-Hernandez et al., 2008a).

Fig. 2. (Top) Down-looking antenna used to measure the reflected signaland (bottom) measured radiation pattern.

2.2. Antenna and RF front-end

The selection of the down-looking antenna is a trade-offbetween directivity and beamwidth. On one hand the direc-tivity must be high enough so as to increase the SNR, andon the other hand the beam must be wide enough so as toobserve the whole glistening zone (i.e. area from wherethere are significant contributions of the scattered powerdisregarding the effect of the antenna pattern). When mak-ing the design, the extent of the glistening zone (defined asthe surface area that contributes to the scattered powerabove 3 dB below the specular reflection point contribu-tion) for a height of 400 m, and a moderate wind speedof 10 m/s has been estimated to have a diameter on theorder of 200 m which lead to a beamwidth around 20�.The down-looking antenna has to be left hand circularlypolarized (LHCP) as it is the main polarisation of thetransmitted right hand circular polarized (RHCP) signalafter scattering on the surface. The antenna used in theimplementation of griPAU is an array of hexagonal 7LHCP microstrip patches. This antenna has a measuredbeamwidth of 22�, a main beam efficiency of 90.5% and again of 16.2 dB (Fig. 2).

To avoid the modulation of the measurements by theantenna radiation pattern as the GPS satellite moves, theantenna down-looking is mounted on an automatic posi-tioning system that performs a dynamic tracking of thespecular reflection point over the observation surface. Thiseffect is observed in Fig. 3(top) where the antenna was stilland the measured DDM peak for different satellite pas-sages is represented as a function of the elevation angle.Moreover, in Fig. 3(bottom) the antenna has been pointedtowards the specular reflection point when the satellite ele-vation was 26� and kept fixed during the capture. It is seenhow the DDM peak, which is proportional to receivedpower, decreases to half its maximum value (i.e. �3 dB)as elevation goes down from 26� to 15� which correspondsto a movement of half the beamwidth from the antennaboresight.

Once the direct and reflected signals have been collected,they are amplified, filtered, down-converted, and sampled.The receiver used in griPAU is the one that has been devel-oped in the frame of the PAU project (Ramos-Perez et al.,2006). This receiver has two chains with 120 dB gain,2.2 MHz bandwidth, and the output signal is centered atan intermediate frequency of 4.309 MHz, and the samplingfrequency is 5.745 MHz.


2.3. Signal processor

The griPAU instrument signal processor (Fig. 4) hasbeen designed and implemented using the digital hardwareresources of a Xilinx Virtex 4 FPGA. The design has beencarried out to achieve two main objectives: (1) to take themaximum benefit of the available resources, and (2) to keepa strict control of all the timing and synchronism rules so asto implement a system as stable as possible.

A high level block diagram of the signal processor imple-mented for the griPAU instrument is shown in Fig. 5. ThegriPAU signal processor has three signal paths: two for thedirect signal and one for the reflected. One of the direct signalchains is connected to the Trimble GPS receiver to obtain thesignal’s Doppler frequency offset. The second direct signalchain is used by the signal processor embedded in the FPGAto estimate the signal’s delay after the RF front-end, sam-pling and demodulation. Once the delay and Doppler offsetsare known, the DDM generator core uses the demodulatedand sampled reflected signal to compute the Delay-DopplerMap. Since the FPGA clock frequency is much higher thanthe sampling frequency, hardware reuse techniques can beused to dramatically reduce the hardware resources needed,



Fig. 3. (Top) Antenna pattern modulation for different satellites vs.elevation angle, (bottom) DDM maxima is modulated by the antennaradiation pattern when the antenna is kept in a fixed position. Quickoscillations are due to multi-path in the cliff and geophysical variability ofthe observables.


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or alternatively, to increase the size of the computed DDMwith the same hardware resources.

The up- and down-looking signal paths to be processedare conditioned and sampled at 8 bits with a sampling fre-quency of 5.745 MHz. Since the IF is 4.309 MHz, band-pass sampling can be used, and the signal is centered at a

Fig. 4. griPAU sig


digital frequency of 0.25. At this digital frequency the tonesneeded to I/Q demodulate the input signals can beexpressed using only two bits and the digital I/Q demodu-lation can be performed very efficiently by using simple log-ical functions instead of multi-bit multipliers (Marchan-Hernandez et al., 2008a).

Once the signals have been I/Q demodulated, a digitallow-pass filtering stage has been implemented to eliminateundesired high frequency components. This filter has alsobeen designed to use the lowest possible amount ofresources. To achieve that, an IIR filter topology with onlypower of two coefficients has been designed so that multi-plications and divisions are transformed into left-shiftand right-shift operations avoiding again the use ofresource-consuming multipliers and dividers (Bosch-Lluiset al., 2006). At this point the main processing starts. Totake advantage of hardware reuse techniques, the dataacquired during a basic integration time (1 ms) is stored,so it can be read several times. The main blocks that allowthis technique to be successfully dealt with, are the controlunit and the data buffer (Fig. 5).

The hardware control unit is based on a finite statesmachine (FSM) built to replace the software control usedin previous versions to have a tight control of the timingof the hardware reuse technique. One fourth of the com-plete DDM is computed at a time, and using the samehardware, the four DDM quadrants are serially computedduring four time slots. All this process takes place in 1 mswhich is the duration of the C/A code and the basic inte-gration time. Replacing the software control unit by aFSM has improved the synchronization of the four quad-rants allowing to increase the size of the DDMs signifi-cantly (from 16 � 16 to 24 � 32 bins in the Virtex4implementation) leading to a more stable system. Fig. 6shows two DDM captions: in the first one a synchronismproblem has occurred, while in the second one, computedwith the described architecture, all the DDM parts arealways perfectly aligned due to the high reliability of thehardware synchronism of the control unit.

Also a new data buffer has been implemented to avoidmemory swapping and minimize timing problems. Thisnew buffer is based on a dual-port RAM memory which

nal processor.



Fig. 5. Block diagram of the griPAU signal processor.

Fig. 6. Sample 1 ms DDMs: (top) synchronism problem occurred duringthe acquisition translates in misalignment of the four quadrants (hardwarereuse), and (bottom) synchronism problem solved.


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has a depth twice the size of the I–Q data sampled in 1 ms.With this implementation, the memory is divided in twozones, so when one half is written by the writing port,


the data stored in the other half is read by the reading portand processed. Each millisecond the two halves exchangetheir roles without any physical memory swapping anddata is properly updated.

The delay estimation algorithm has been optimized lead-ing to a reduction of the update time from 16 to 5 ms, allow-ing griPAU to track signals even in high dynamics scenarios.The delay estimator core is basically the one implemented inprevious versions (Marchan-Hernandez et al., 2008a), usinga FFT approach, Eq. (4). Due to the zero-padding needed toadapt the number of samples (5745 samples) of the data tothe next power of two (8192 samples), two correlation peaksappear. The griPAU implementation has improved this coreperformance avoiding peak detection errors by applying athreshold to check whether the returned delay is a validone or if it corresponds to the secondary peak of the cross-correlation. If so, the known distance between peaks (in sam-ples) is subtracted to get the correct delay value.

Fig. 5 shows that the signal processor implements also amicroprocessor. In the implementation of griPAU thismicroprocessor has been relegated just to interface theTrimble GPS, and to perform floating-point operationsthat would consume too many resources if implementedin hardware. Notice that all the timing and synchronismresponsibilities have been transferred to the FSM controlunit, for improved robustness in front of the uncontrolledtiming of operative systems.

The last block of the griPAU signal processor is theDDM generator core which has remained essentially thesame as in previous versions of the instrument (Marchan-Hernandez et al., 2008a). This block generates each ofthe four DDM parts at a time and is controlled by the con-trol unit so as to implement the hardware reuse.

2.4. Clocking scheme

When designing griPAU, the stress has been put on pre-serving the phase coherence among all the system’s clocksto prevent undesired decorrelation effects. The clocking pol-icy has been redefined using an oven-controlled 10 MHz sta-bilized reference (Fig. 7), and the FPGA-built processor hasbeen modified to work with the 103.41 MHz clock (instead of



Fig. 7. griPAU clocking scheme.


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the original 100 MHz one) which is a direct multiple of thesampling frequency.

The final clocking scheme divides the single 10 MHz sta-ble reference in two branches: one branch is used as the RFfront-end reference for the phase-locked loops, and theother one is doubled in order to be the reference of a DirectDigital Synthesis (DDS) device that generates a very accu-rate 103.41 MHz clock reference for both sampling andprocessing in the FPGA. The accurate sampling frequencyand perfect synchronism avoid artificial delay drifts causedby different chip lengths among the sampled signal and thelocal replica of the C/A code generated in the processingstep, resulting in very high stability.

2.5. Data output

Every 1 ms, griPAU computes one complex DDM of24 � 32 bins. Each bin is a complex number with its realand imaginary parts quantified with 32 bits, which leadsto a total data output rate of 6.14 Mbps. This throughputis delivered to an external PC via an USB interface.

Using a graphical interface executed in the external PC,the user can control the instrument configuration (satelliteto be tracked, capture length, etc.) and the computed datacan be stored in raw format or further averaged by meansof a selectable coherent/incoherent integration times.

3. Instrument performance and trade-offs

3.1. Delay estimation

Relating to the direct signal path used for delay estima-tion, a study has been undertaken to improve the final esti-mation error rate (i.e. increasing the signal’s SNR). Sampleresults of the three approaches tested are shown in Fig. 8.The first delay estimator uses only the in-phase signal (I).The second one uses both the in-phase and quadrature(Q) components of the direct signal to improve its robust-ness in front of noise, multi-path, as well as preventing sig-nal fading due to phase rotation. This has the drawback ofincreasing the hardware resources (multipliers) needed ifonly the in-phase component is used. The third and moreefficient approach works with both I/Q components anduses a wide-beam RHCP antenna instead of a single linear


polarisation one to improve the robustness of the signal infront of undesired reflections and multi-path.

To validate the improvements implemented in the delayestimation algorithm, real GPS direct signal captures havebeen performed. Real signal has been used to test the sys-tem when all the effects, such as undesired reflections andmulti-path, are present. Fig. 8 shows the delay estimationperformance as a function of the algorithm implemented.The performance is nearly perfect for the last configura-tion. It is seen that, if the error rate is defined as the num-ber of errors per number of measurements, it is reducedfrom 6.7% when only the I component of the signal is pro-cessed, down to 1.7% when both I/Q components are pro-cessed, using all the signal’s available power, and down to anearly negligible value of 0.03% when multi-path is avoidedby using a RHCP antenna.

The fast linear evolution (two complete code lengths in1 min) of the delay is due to the inaccuracy of the samplingfrequency which causes a difference between the chiplengths of the received signal and the local replica. Thisartificial delay evolution is overcome when the new clock-ing scheme is applied as the clock reference given by theDDS allows the signal processor to generate a very accu-rate sampling frequency. With the ultimate griPAU imple-mentation, only the true delay evolution is observed as inFig. 9.

3.2. Delay-doppler map size and resolution

Although using a very accurate sampling frequency andavoiding potential artificial delay drifts, the residual differ-ence between the actual sampling frequency and the theo-retical one considered at processing, still causes somemeasurements’ variance due to the variable DDM discretesampling points (i.e. the delay estimation is not able to dis-tinguish subsample variations).

This effect is deterministic, and the relationship of thefinal DDM amplitude variation with the resolution ismonotonically decreasing, so the variance can be reducedby reducing the DDM cell size in the delay dimension.Also, if the DDMs are not to be truncated, the total DDMssize has to be increased. In the design and implementationof griPAU, the system has been rearranged in order to takeadvantage of all the FPGA resources, so the total DDMsize has been increased from 16 � 16 points up to 24 �



Fig. 8. Delay estimation performance for different estimator algorithms, (top) using only the in-phase (I) component (6.7% error rate), (center) using in-pase and quadrature components (1.7% error rate) and, (bottom) using I and Q components and a RHCP antenna to receive the direct signal (0.03% errorrate).

Fig. 9. Delay evolution measured using the new clocking scheme. Error rate is nearly negligible.


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32 points allowing to compute the DDMs with a delay res-olution as low as 0.5 samples (0.09 chips) (Fig. 10), so the


measurements’ variance due to shifts in the DDM peak’sposition in delay, in amplitude as well as in normalized



Fig. 10. Sample 24 � 32 points, 0.09 chips resolution, 1-ms DDMmeasured over the ocean surface from a 382 m height.


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DDM volume (see Section 1), is significantly reduced. Therelationship among these variances and the delay resolu-tion has been studied.

Using a GPS synthetic signal three series of DDMshave been computed configuring the instrument withthree different delay resolution values (2, 1, and 0.5 sam-ples corresponding to, 0.36, 0.18, and 0.09 chips, respec-tively) while keeping the Doppler resolution constant(200 Hz) (Fig. 11). The effect of variable DDM sampling

Fig. 11. DDM normalized volume vs. DDM resolution measured using asynthetic GPS signal to avoid multi-path and other error sources: (top)Ds = 2 samples (0.36 chips), (center) Ds = 1 sample (0.18 chips) and,(bottom) Ds = 0.5 samples (0.09 chips).


points is clearly observed, both in the normalized volumeand the maximum value when a coarse resolution of 2samples is used. These values present an evolutionbetween two extreme values which correspond to theDDM sampled at the true maximum and at 2 samplesaway from it. This effect is reduced when 1 sample reso-lution is used and it can be nearly neglected when theDDM is computed with 0.5 samples resolution. With thisfine resolution, the measurement’s variance is only due tothe system’s noise. As it can be appreciated in Fig. 11,the normalized DDM volume and the maximum modulepresent (in a stronger way when using poor resolutions)a kind of “triangular” modulation originated by the lin-ear evolution of the time delay between the true DDMpeak and its adjacent sample.

3.3. Instrument’s sensitivity and stability

When operating in the normal mode, 1 s incoherentlyintegrated DDMs are measured. Setting the DDM resolu-

Fig. 12. DDM 1-s incoherently integrated (top) volume (relativeerror = 0.03%) and, (bottom) peak module (relative error = 0.9%).



Fig. 13. Normalized autocorrelation of the complex DDM maximum.


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tion to 200 Hz in Doppler and 0.5 samples (0.09 chips) indelay, the measurements (Fig. 12) have a very small stan-dard deviation (0.9% of the DDM peak value and 0.03%of the normalized DDM volume – maximum value equalto one, units [chips � Hz]). This error determines the reflec-tometer’s sensitivity (i.e. the minimum DDM peak or nor-malized DDM volume variations that can be detected ormeasured by the instrument).

In order to evaluate the system’s performance concern-ing the correlation time of the coherently integrated mea-surements a synthetic GPS direct signal has been used.As this signal is simply a GPS C/A code up-converted toRF, its correlation with the local replica should be con-stant. However, system inaccuracies and noise cause someresidual decorrelation of the measured DDMs when coher-ent integration is performed. To evaluate this parameter(i.e. DDM decorrelation time due to the instrument), theevolution of the DDM’s maximum is studied. Results areshown in Fig. 13. For instance, if the time that the mea-surements decorrelate to a 90% of the maximum is consid-

Fig. 14. griPAU during the: (left) ALBATROSS 2009 and (Gran Canaria, Canfield experiments.


ered, the instrument can perform coherent integration upto 100 ms (Fig. 13). Taking into account that at L-bandthe sea correlation time is estimated to be of the order oftens of milliseconds (Chapman et al., 1994), the griPAUcan be used to the study of physical phenomena of thesea surface that require coherent integration or phase infor-mation. This is a significant improvement result of the largeeffort carried out in the system’s synchronism, samplingfrequency accuracy, and improved clocking scheme.

4. Sample measurements

The griPAU instrument has already been used in twofield experiments (Fig. 14): the Advanced L-BAnd emissiv-iTy and Reflectivity Observations of the Sea Surface 2009(ALBATROSS 2009) over the ocean in Gran Canaria(Canary Islands, Spain) (Valencia et al., 2009) and GPSand RAdiometric Joint Observations (GRAJO) (Monerriset al., 2009) over land (Vadillo de la Guarena, Zamora,Spain). Over the ocean griPAU has been used to studythe derivation of sea roughness from GNSS-R measure-ments, and how to correct the sea state effect on the bright-ness temperature measurements acquired by an L-bandradiometer (Valencia et al., 2009). Over land, griPAU hasbeen used for soil moisture retrieval in conjunction withthe SMIGOL reflectometer (Rodriguez-Alvarez et al.,2009) and also with the LAURA radiometer (L-bandAUtomatic RAdiometer) (Camps et al., 2004b). Howeverthe raw data from this last experiment has not yet beencompletely processed.

In order to illustrate the griPAU instrument perfor-mance given in this paper, some relevant sample measure-ments related to the instrument performance are shown.The presented measurements correspond to the basicobservable computed by griPAU which are 1-ms coher-ently integrated complex DDMs.

Fig. 15 shows a histogram of the DDM maximum mod-ule resulting from a 60 s capture of 1-ms complex DDMs(60,000 complex DDMs) taken during the ALBATROSS2009 field experiment (Valencia et al., 2009). The main

ary Islands, Spain) (right) GRAJO (Vadillo de la Guarena, Zamora, Spain)



Fig. 15. Histogram of the 60,000 samples of DDM module maximaduring a 60 s capture of 1-ms complex DDMs shows a Rice behaviour.


ARTICLE IN PRESS

observation scenario parameters for this capture were: aheight of 382 m, an elevation angle of 26� and a WS of2.1 m/s. As it can be seen, this histogram presents a Ricebehaviour (Rice parameters: A = 3.5 � 105 andr = 2 � 105) which is the probability density functionexpected for a GPS signal scattered over a sea surface whena coherent contribution from the first Fresnel reflectionzone is present.

For the same capture, a detail of the phase of the DDMmaximum (i.e. the phase of the coherent contribution tothe scattering process) is plotted in Fig. 16. It can benoticed that this phase exhibits random p-rad phase jumpsat multiples of 20 ms. These phase jumps are due to thepolarity inversion of the navigation bit (Eq. (2)), showingthe excellent sensitivity of the griPAU instrument, whichis able to detect the navigation bit even when processingthe reflected GPS signal over the ocean surface.

Fig. 16. Phase evolution of the DDM maxima.


5. Conclusions

Emerging GNSS-R remote sensing techniques havebrought out the need of implementing adequate and robustreceivers. In this paper the design and implementation ofthe GPS Reflectometer Instrument for PAU (griPAU) ispresented, as well as some relevant measurements showingits performance.

The griPAU computes high resolution complex Delay-Doppler Maps in real-time. The computed DDMs are24 � 32 points with configurable resolution as well asselectable coherent (minimum = 1 ms, maximum = 100 msfor correlation loss Dq < 10%) and incoherent (minimumof one coherent integration period and not limited maxi-mum, typically <1 s) integration time. Its design hasfocused on achieving an extremely stable and sensitiveinstrument making the best use of the digital hardwareresources of a FPGA, and taking exquisite care of synchro-nism and phase coherence. Concretely, the stability of theinstrument allows to coherently integrate up to more than100 ms (correlation loss Dq < 10%) which is much longerthan the ocean’s correlation time at L-band, thus enhanc-ing the system to perform deeper studies about the ocean.Moreover, the achieved instrument’s sensitivity (DDMpeak relative error = 0.9% and DDM volume relativeerror = 0.03% @ Ti = 1 s) will improve the quality of theresults for geophysical parameters retrieval.

This implementation has resulted in a fully operationalreal-time complex DDM GNSS-R instrument that hasalready been used in field experiments over sea and land,with very promising results.

Acknowledgements

This work, conducted as part of a EURYI (EuropeanYoung Investigator) Award, 2004, was supported byfunds from the Participating Organizations of EURYIand the EC Sixth Framework Program. It has also beensupported by research project AYA2008-05906-C02-01/ESP

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