THE EFHRAN PROJECT
Paolo Ravazzani Istituto di Ingegneria Biomedica Consiglio Nazionale delle Ricerche Milano
Interactions of RF with the human being State of knowledge Jeudi 18 Dcembre 2008
Executive Agency for Health and Consumers EAHC Health 2008 Programme - Second programme of community action in the field of health (2008- 2013) EFHRAN European Health Risk Assessment Network on Electromagnetic Fields Exposure Starting date: February 1, 2009 Ending date: January 31, 2012

PARTNERS

Istituto di Ingegneria Biomedica CNR - Italy

Paolo Ravazzani

Fundaci Centre de Recerca en Epidemiologia Ambiental (CREAL) - Spain

Elisabeth Cardis

Universit degli Studi di Genova - Italy

Guglielmo DInzeo

Institute of Nonionizing Radiation - Slovenia

Peter Gajek

Kraeftens Bekaempelse (Danish Cancer Society) - Denmark

Joachim Schz

Health Protection Agency United Kingdom

Zenon Sienkiewicz

National "Frderic Joliot-Curie" Research Institute for Radiobiology and Radiohygiene - Hungary

Gyorgy Thuroczy

Laboratoire de l'Intgration du Matriau au Systme, UMR 5218 CNRS - France

Bernard Veyret

. and Collaborating partners

GENERAL OBJECTIVES

To establish a European health risk assessment network on EMF. Strategic objectives: Monitor and search for evidence of health risks related to EMF exposure. Characterize and, where appropriate, quantify potential health risk posed by EMF exposure. Enhance the EC's ability to respond rapidly to health issues and concerns related to EMF using scientifically sound advice and analyses. Improve the compilation of knowledge and its dissemination on issues related to EMF and health.

OBJECTIVE 1

To monitor, analyse and identify health risks due to EMF exposure on the basis of human studies.
To monitor and review key research results on the possible effects of exposure of humans to EMF and to identify any potential EMF health risks.

OBJECTIVE 2

To monitor, analyse and identify health risks due to EMF exposure on the basis of in vitro/in vivo studies
To monitor and review key research results from in vivo/in vitro (animals) studies to identify any EMF health risks.

OBJECTIVE 3

Quantitative EMF exposure assessment
To estimate the amount, duration, and pattern of exposure to EMF from various sources.

OBJECTIVE 4

Exposure-response assessment and related metric on EMF exposure
To estimate the magnitude of possible risks due to exposure to electromagnetic fields, considering their pattern and modulation

OBJECTIVE 5

Risk characterization and related indicators
To characterize population risks, using information on exposure response and exposure distribution obtained within the project

OBJECTIVE 6

Input to communication and risk management processes
To identify priority areas for immediate intervention where appropriate. Identify main needs for risk communication.
EMFNETCoordinationAction 20042008
EMFNET Bruxelles,May30,2008

EMFNET:afewnumbers

Contractors:38 Additionalinterestedbodies:14 Involvedcountries: 19 Technicalworkinggroups:19plusEFRT Involvedexperts: 85

EMF-NET: a few facts

Interpretationreports: 60 Factsheetsandshortreport: 30 OtherreportsandsupporttoECservices: 15 Organization/coorganizationofevents: 30 Interviews,PressReleases,etc:around15 Scientificpublications:3(plusone)booksand1SpecialIssueof Bioelectromagnetics Otherpublications: catalougueofECFP5researchonEMFand health
WORKSHOP on Current Trends in Health Risk Assessment of Work-Related Exposure to EMFs
MILAN, FEBRUARY 14-16, 2007 http://www.icnirp.org co-organized with
2 WORKSHOP on EMF Risk Communication: Effective Risk Communication in the Context of Uncertainty
Stresa, Maggiore Lake, Italy, May 2 - 4, 2007 http//emf-net.isib.cnr.it
EUROPEAN COMMISSION DIRECTORATE GENERAL JRC JOINT RESEARCH CENTRE

Electromagnetic Field Exposure: Risk Communication in the context of Uncertainty
Editors Carlos del Pozo Demosthenes Papameletiou Peter Wiedeman Paolo Ravazzani Emilie van Deventer
The Universe is a grand book which cannot be read until one first learns to comprehend the language and become familiar with the characters in which it is composed Galileo Galilei
http://emfnet.isib.cnr.it

Development of a One Channel Galileo L1 Software Receiver and Testing Using Real Data
F. Macchi and M.G. Petovello Position, Location and Navigation (PLAN) Research Group Department of Geomatics Engineering Schulich School of Engineering University of Calgary
BIOGRAPHY Florence Macchi is a PhD candidate in the department of Geomatics Engineering at the University of Calgary, Canada. She is a member of the PLAN Group (Position, Location and Navigation). She completed her bachelor of electrical engineering in 2006 in the INT (Institut National des Telecommunications), France. She is currently working on Galileo and receiver design. She expects to finish her PhD in September 2009. Dr. Mark Petovello is a senior research engineer in the Position, Location and Navigation (PLAN) group where he executes and supervises various navigation-related projects. Since 1998, he has worked on several projects including satellite-based navigation, inertial navigation, reliability analysis, dead-reckoning sensor integration, and most recently, software-based GNSS receivers. ABSTRACT With the recent or upcoming availability of several new signals from GPS, Galileo, GLONASS and Compass, the beginning of a new era in the field of GNSS has arrived. The recent development and launching of the first Galileo satellite GIOVE-A, part of the Galileo System Test Bed as well as the still on-ground testing satellite GIOVE-B is the start of this new age. Therefore, with such an improvement in the number of signals available to the user and the geometry offered by the combination of the various constellations, the current capabilities but also complexities of the receivers will be increased. One challenge is of course the acquisition and tracking of Galileo signals, especially using the actual data transmitted by the current orbiting satellite GIOVE-A. Due to the properties of the new L1 Galileo signal, novel acquisition techniques need to be developed. Beginning with the common zero padding technique, four new techniques of acquisition are described and implemented.
The four acquisition methods (two for each the pilot and data channel) are then tested and compared in terms of processing time and acquisition sensitivity. Then, a tracking algorithm is presented using common strategies and the parameters of the filters are studied. All these tests are realized using real data from the current Galileo satellite. The two methods of acquisition using a longer incoming signal permit an improvement of the SNR of 5 dB for the data channel and 4 dB for the pilot channel. But these new strategies require more processing time and thus should be used only for weaker signals. The results of acquisition and tracking are validated using a NovAtel 15a receiver for comparison.
INTRODUCTION The European Commission (EC) and the European Space Agency (ESA) has been collaborating in Galileo to create the first European global navigation system. This new Global Navigation Satellite System (GNSS) is mainly civilian and commercial - except the PRS (Public Regulated Service) which will is reserved for the public authorities - and will be inter-operable with GPS and GLONASS, the American and Russian GNSSs. The first Galileo satellite, GIOVE-A was launched on 28 December 2005 and is being used to test the equipment of the satellite and the ground stations and to secure the Galileo frequencies within the International Telecommunications Union. At the end of 2007 is scheduled the launch of the second test satellite GIOVE-B to continue the tests and incorporate some improvements. Another test satellite, GIOVE-A2 will be ready for launch in the second half of 2008 to secure the frequency in case of a malfunctioning of the two other satellites (European Space Agency ESA website).

The ranging codes are longer than for the C/A L1 GPS signal, so it reduces the cross-correlation products, but the acquisition time is longer. The secondary code on the pilot channel has two main advantages: It helps achieve data synchronization It increases the signal resistance to narrow-band interference

Figure 4: BOC modulation

The L1-B and L1-C signals can be expressed as follows (GIOVE-A SIS ICD 2007):

eL1 B =

rectTC ,L1 B e L1C =

[c (t i T

+ L1 B , i + L1 C , i

LL 1 B

d L1 B ,[i ]DC
power. Then, IF samples were recorded using a NovAtel Euro3M Card. At the same time, the pseudorange, Doppler and C/No, measurements were recorded from a NovAtel 15a receiver for comparison purposes. Figure 5 shows the data collection setup.

External Oscillator

C , L1 B

) sign[sin (2 R

S , L1 B

[c sign[sin (2 R

L L 1 C
rectTC , L1 C (t i TC , L1C ) t )]]

Antenna

S , L1C

Euro3M Card

IF samples
and the total baseband signal on L1 (without L1-A) is:

s L1 =

1 [eL1 B (t ) eL1C (t )] 2
using the following notations: eL1 B and eL1C are the L1-B and L1-C signals, including the code, the modulation and the data cL1 B , i and cL1C , i

15a receiver

Measurements

subcarrier,

Figure 5: Test set-up The Euro3M Card has the following characteristics: Records real samples at 40 MHz (equivalent to 20 MHz complex samples) Intermediate frequency is 70.42 MHz on L1 Output used is one bit quantization on L1 Front-end bandwidth of 16 MHz (two-sided) As shown in Figure 6, an external rubidium oscillator (10 MHz) was used to drive the NovAtel Euro-3M. A rubidium oscillator was selected to remove any significant oscillator effects on signal tracking performance. Future tests will include poorer quality oscillators.

are the ranging

codes of L1-B and L1-C d L1 B ,[i ]DC is the navigation message
rectTC (t ) and is rectangle function (defined to
equal to one between 0 and Tc) RS , L1 B and R S , L1C are the subcarrier
frequencies of L1-B and L1-C (used in the BOC modulation) here RS , L1 B = RS , L1C = 1.023MHz This modulation has an important impact on the correlation of the signal: in addition to the main peak, side peaks are generated at half a chip on each side of the main peak with half the power of the main peak. These two side peaks have an impact on the tracking as explained later. TEST PROCEDURE Currently, there is only one Galileo satellite in the sky, the GIOVE-A. Therefore, this satellite has been used to test all the algorithms developed hereafter and to compare the performances of the data and pilot channel. The GIOVE-A is able to transmit on only two frequencies at a time. The information about the current Galileo frequencies transmitted can be found on the official GIOVE-A website: http://www.giove.esa.int. The NASA overpass predictor was used to know when the satellite was visible with a good elevation angle. Since in this research the main goal was to develop and test new algorithms, the data were recorded only when the satellite was at a high elevation and so a relatively high signal

External oscillator

PC used for the data collection
Figure 6: Pictures of the data collection
The NovAtel 15a receiver contains 16 channels capable of tracking and decoding GPS L1 and L5, Galileo L1 and E5a and SBAS signals. The receiver configuration used was: 5 Galileo L1 channels 5 Galileo E5a channels 6 GPS L1 channels
METHODS OF ACQUISITION OF THE L1 PILOT AND DATA CHANNELS The acquisition scheme used for all the following acquisitions is a standard parallel code phase search acquisition presented in Figure 7. With this method, the correlation is computed in the frequency domain, which permits a reduction in the processing time compared to an acquisition in the time domain (Borre et al. 2007).
The acquisition is developed for the data channel and then for the pilot channel using 8 ms of incoming signal and 16 ms of incoming signal respectively. This implementation used the zero padding technique (Yang et al. 2004), strategy commonly used for L5 GPS (Mongredien et al. 2006). But to compare the characteristics of the acquisition of the data and pilot channel, it is necessary to have the same length of incoming data. Thus, beginning with the zero padding technique, two new methods of acquisition are created and implemented to acquire the pilot channel using 16 ms of incoming signal and the pilot channel over 8 ms. As mentioned before, the usual techniques of acquisition for GPS L1 cant be applied to the Galileo L1 signals due to the properties of the signal. On L1-B the sign of the bit of the navigation message can change each ranging code period, so if the integration is done over two (or more) ranging code periods, a destructive combination can occur leading to degraded acquisition performance. The same problem is encountered in the case of L1-C even if there is no navigation message, the secondary code plays the same role: the sign of the secondary bit can change each time the ranging code repeats. The difference with L1-C however, is that the structure of the secondary code is known, and once the receiver is synchronized with the secondary code, it can be effectively removed. Four acquisition techniques have been developed for this paper, two for each the pilot and data channels. The algorithms are compared in terms of sensitivity and processing time. First, an acquisition strategy was developed for the data channel L1-B using 8 ms of incoming signal. If the correlation is realized only over the length of one spreading code period (i.e. 4 ms), it is possible that no correlation peak will be visible if a change of sign happens in the incoming signal. Since the correlation is done in the frequency domain, a zero padding strategy is needed. This strategy has already been implemented in the case of GPS L5 for example in Mongredien et al. (2006): Take 8 ms of incoming sample data. A local replica of the complete ranging code (4 ms for L1-B) is created and padded with 4 ms of zeros. The correlation is performed If the correlation is done on the 8 ms, one or two peaks will be generated depending on the sign change in the bit of the navigation message (see Figure 8). However, a correlation peak will always be present in the first 4 ms of output, so only this part of the correlation result needs to be searched. Furthermore, the first peak is always higher or of the same amplitude as the second

Figure 7: Parallel code phase search acquisition scheme Since the first Galileo satellite has been launched, some research has been done about the acquisition and the tracking of the Galileo L1 signals. Nevertheless, few of the algorithms implemented have been tested with real data, instead using signal simulators. Indeed, Marradi et al. (2006), Spelat et al. (2006) and Botteron et al. (2006) have developed Galileo receivers or algorithms of acquisition and tracking but tested them only through the use of signal simulators. Few people such as Ledvina et al. (2006) have implemented algorithms and Galileo L1 receiver and have tested it using real data, but their main goal was to create it in real time and not to compare the performances of the signals using different algorithms. Finally, Psiaki et al. (2006) have developed a statistical technique to decode the code before their release. In this research, new methods of frequency-domain acquisition are proposed to acquire the pilot and data channel using different length of incoming signal, adapted to the strength of the signal. Then, the parameters of the filters of a traditional tracking are studied to optimize the tracking performances.
peak because it always represents a correlation of the entire spreading code period.
highest one, so the correlation peak need to be searched only in the first 8 ms To compare the performances of the pilot and data channel, the acquisition of the data channel is done as well using 16 ms of incoming data. In this case, the zero padding technique as presented above cannot be used anymore. Indeed, in the case of the data channel, in 16 ms of data it is possible to have three changes in the sign of the data bit. Thus, if the same zero padding technique is used: If one spreading code period only is used and padded with 12 ms of zeros, there will be no gain in using 16 ms of data instead of 8 ms. If two or more spreading code periods are used and padded with zeros, a destructive combination can occur and the acquisition can be highly degraded. Therefore, an adaptation of the technique has been created and implemented to realize an acquisition of the data channel using 16 ms of incoming signal. Since 16 ms of incoming signal are considered, there are four possible values in the sign of the bit of the navigation message. To accommodate this, the acquisition is realized using four different sub-groupings of the incoming signal, each 8 ms long, as shown in Figure 9. In all cases, the local code consists of 4 ms of the ranging code (i.e., the full code) padded with 4 ms of zeros. The four sub-groupings of the incoming data are defined as follows: First, the first 8 ms of incoming signal are considered. Second, the first and last 4 ms of incoming signal are not considered (only the 8 ms from the fifth to the twelfth millisecond are used). Third, the last 8 ms of incoming signal are considered. Finally, the last 4 ms of incoming signal are combined with the first 4 ms of incoming signal. The results of these four correlations are finally added. This method allows to acquire the signal using 16 ms of incoming signal, but it requires much more operations (and so more processing time) than the previous one. Consequently, this method should be used only in the case of weaker signals, where the first method does not provide a correlation peak strong enough to confidently identify the presence (or absence) of a signal. This method is equivalent to a non-coherent accumulation in the time domain of four times 4 ms. Nevertheless, if this method has to be implemented in a hardware receiver, the four correlations can be performed using four parallel correlators and in this case it will not be longer than the previous method, it will only use a higher number of correlators. However, these correlations may not necessarily be easy to perform in real time, and a solution using buffers may have to be explored.

Legend:

Figure 8: Illustration of the zero padding technique Since on the pilot channel the ranging code lasts 8 ms, it is possible to use as well a zero padding technique (similar to the one used to acquire the data channel using 8 ms of incoming signal) to acquire the signal using 16 ms of incoming data. The acquisition technique used on L1-C to acquire the signal on 16 ms is the following: 16 ms of incoming data are used A local replica of 8 ms of code is created (so one entire spreading code period) and is padded with 8 ms of zeros The two signals are correlated If the correlation is done on the 16 ms, one or two peaks will be generated depending on the sign change in the bit of the navigation message (see Figure 8) As before, a correlation peak will always be present in the first 8 ms and will always be the
Legend: Figure 9: Illustration of the technique of correlation over 16 ms for the data channel Finally, another method of acquisition has been created to be able to acquire the pilot channel using 8 ms. Indeed, if the acquisition wants to be realized on the L1-C channel using only 8 ms of data (to compare with L1-B and to decrease the processing time) another problem is encountered: one entire primary code is present in 8 ms of data but a change in the sign of the bit of the secondary code is possible. Thus, if a usual method of correlation is used in correlating directly with a replica of 8 ms of the code, it is possible to have no correlation at all or a very small peak. Therefore, a new method has been created and implemented to avoid this problem. The correlation is done in two steps (see Figure 10): Generation of the first half of the primary spreading code period (so 4 ms) padded with 4 ms of zeros is correlated with the 8 ms of incoming signal Generation of the second half of the primary spreading code period (so 4 ms) padded with 4 ms of zeros is correlated with the 8 ms of incoming signal Then the two correlation results are added over 8 ms With this method, one peak is always present in the 8 ms of correlation. In the case of the implementation in a software receiver, it increases the number of operations and processing time (compared to L1-B), but in the case of the implementation in hardware, the two steps can be done simultaneously in parallel using two different correlators, and thus the time processing will not be increased.

Figure 10: Illustration of the technique of correlation over 8 ms for the pilot channel
RESULTS OF THE ACQUISITION METHODS AND COMPARATION The software receiver was developed in two main parts: at first the acquisition has been implemented in Matlab, then the acquisition has been integrated into a modified version of the GSNRx software for the tracking part (Petovello and ODriscoll 2007). In the following, the result of the processing of the data recorded from the GIOVE-A satellite on April 16, 2007 is presented. During data collection, the satellite had an elevation angle of about 65 degrees. The samples are then processed using the software developed. In the case of the data channel (L1-B), when the acquisition is realized using 8 ms of data, two main correlation peaks were observed as illustrated in Figure 12. As explained in the previous section, the first peak is higher than the second one due to (potential) destructive combination in the second peak. For the data in Figure 12, the code delay between the incoming signal and the local replica is small (about 279.7 chips) thus if there is a destructive combination due to the change in the sign of the data bit, it is relatively small. As seen on the graph,
the second peak is only a little bit smaller than the first one. Some other important properties can be mentioned about this three dimensional graph: There are exactly 4092 chips between the two peaks, which represents the length of the primary code on L1-B The two peaks are at exactly the same Doppler frequency The previous observations are necessary properties of this acquisition but needed to be checked to validate the results.
The increase in the size of the peak for the 16 ms case (an analysis of the SNR is presented later) costs a lot of processing time: it takes around three times longer to process the acquisition over 16 ms than over 8 ms. Nevertheless, the acquisition method over 16 ms has several advantages : It is possible to acquire weaker signals (like indoor or in an urban environment). Indeed, there is an improvement of 5.5 dB between the two methods when the length of the incoming signal is doubled. If it is developed in hardware, four correlators can be used in parallel to do the four correlations and in this case the processing time will be the same as in the case of the acquisition over 8 ms.
Figure 12: Acquisition of the data channel using 8 ms of incoming signal This verification has been done on the all four methods of acquisition and the Doppler frequencies found are the same as the Doppler found with the NovAtel 15a receiver. In the four following Figures (Figures 13 to 16) are the outputs of the acquisition algorithm at the Doppler frequency where the maximum correlation occurs at -300 Hz. All the results of the acquisition are obtained using the same set of data. Figures 13 and 14 represent the acquisition results for the data channel using respectively 8 ms and 16 ms of incoming signal. Comparing the acquisition results of the data channel over 8 ms and 16 ms shows some differences but also the common points are clearly visible. In both graphs, the first peak (at around 638 chips) is higher than the second (at around 4730 chips) one due to destructive recombination (as explained before) and a difference of 4092 chips is observed between both peaks, which represent one spreading code period. The position of the peaks is exactly the same for the two different times of integration: same Doppler frequency and same code delay. Thus, with these conclusions, these two methods of acquisition can be validated. Figure 13: Results of the acquisition for the data channel using 8 ms of incoming signal

Figure 14: Results of the acquisition for the data channel using 16 ms of incoming signal Figures 15 and 16 represent the acquisition results for the pilot channel using respectively 8 ms and 16 ms of
incoming signal. As before, comparing the acquisition results of the data channel over 8 ms and 16 ms shows some differences but also some similarities. In the first graph, there is only one peak since the length of the code is 8 ms and the acquisition is implemented on 8 ms (the length of spreading code period). The peak and thus the code delay is at the same place using both methods of acquisition of the pilot channel. Moreover, these results are in accordance with the ones of the data channel: the code delay found is exactly the same for the data and pilot channels.
Since the code delay is relatively small (only around 638 chips), the destructive combination between the parts of the spreading code at the beginning and at the end of the 16 ms is very small, therefore there is mainly one sign of bit of the secondary code
As before, the increases in the size of the peak for 16 ms of integration cost a lot of processing time (it is around two times longer than using 8 ms of data), but it is possible this way to acquire weaker signals since the gain of this acquisition is almost 2 dB compared to the other. Nevertheless, if this last method was developed in hardware, it is possible to use two correlators in parallel to do the two correlations (for the 8 ms of incoming data) and in this case the processing time for the acquisition over 8 ms will be reduced and will be four times than over 16 ms.
Figure 15: Results of the acquisition for the pilot channel using 8 ms of incoming signal

8000 7000

Peak size (ratio) Figure 16: Results of the acquisition for the pilot channel using 16 ms of incoming signal On the second graph (Figure 16), the first peak is almost the same size as the second one. This can have two explanations: The sign of the bit of the secondary code is the same over the 16 ms (so over the two spreading code periods) and thus there is no destructive combination

Code delay (chip)

Figure 17: Detail of the BOC correlation for real data (on the top) and for simulated data (on the bottom) Since one of the main differences between GPS L1 and Galileo L1 is the modulation, it is interesting to look in
more details at the correlation peak in these acquisitions. If the last acquisition (Figure 16) is investigated in more detail (pilot channel over 16 ms), the main peak is clearly visible as well as the two sided peaks at half a chip on each side of the main peak with half of the power of the main peak. As presented in Figure 17, the shape of this BOC modulation is exactly the same as the one for the simulated data. To compare the four different acquisition strategies two parameters have been compared: The acquisition sensitivity The processing time To compare the sensitivity of these four methods of acquisition, a deflection coefficient (form of SNR) has been used:

thus so does the power. The deflection coefficient for the acquisition on 8 ms for L1-C is around 2 dB smaller than on 16 ms for the same channel. Even if the correlation is done two times on 8 ms, the deflection coefficient is smaller than on 16 ms because it is a non coherent correlation on 8 ms and a coherent one on 16 ms. The processing time is almost the same using 8 ms on the pilot and data channel. Nevertheless, the method on L1-B using 16 ms of incoming data is three times longer than on 8 ms. The method using on the pilot channel using 16 ms of data is around two times longer than on 8 ms. These two last methods should be used only for weaker signals. TRACKING OF THE L1 GALILEO SIGNALS Traditional tracking techniques can be used in the case of L1-B and L1-C and are sufficient to have good performance under benign operating environments. Nevertheless, if all the properties of the signal want to be exploited, other techniques have to be applied as the implementation of a pure lock loop for the pilot channel or the combination of the pilot and data channel. These techniques have not yet been implemented but are under development. To track the signal correctly, it is necessary to generate an exact carrier wave replica of the incoming signal. To achieve this, it is possible to use a phase lock loop (PLL) or a frequency lock loop (FLL) or a combination of both. In this project, only a PLL has been implemented. The main steps of the phase tracking algorithm developed are (see Figure 19): Multiplication of the incoming signal with the locally generated carrier to remove the carrier of the input signal Multiplication with the locally generated spreading code to remove the PRN code from the input signal The problem with using an ordinary PLL is the sensitivity to 180 phase shifts. Due to the bits transitions of the navigation message (for the data channel) or the secondary code (pilot channel), the receiver has to be insensitive to 180 phase shifts. Therefore, Costas loop has been implemented. The goal of the Costas loop (and the phase tracking in general) is to keep all the energy in the in-phase component. At the output of the correlators, the Is and Qs are combined using a discriminator (the discriminators used for the PLL and DLL are detailed in the following) and then processed through a filter to reduce the noise. The output of the filter is then converted by the NCO to correct the locally generated phase for the next iteration of the loop.

is the deflection coefficient is the mean value of the main peak is the mean of the noise is the variance of the noise
Deflection coefficient (dB) 5 0

L1-B 8 ms

L1-B 16 ms

L1-C 8 ms

L1-C 16 ms
Figure 18: Comparison of the sensitivity of the four acquisition methods To compute these statistics, thirty separate acquisitions have been performed. As shown in Figure 18, an improvement of 5.5 dB in the deflection coefficient can be observed in the case of L1-B over 16 ms relative to the 8 ms case. Since the correlation is done four times on 8 ms instead of one, an increase of 6 dB should occur, but since the correlation is non coherent in the case of 16 ms, this increase of 5.5 dB is in accordance with the theory. The result for L1-C over 16 ms is 3 dB better then on L1-B on 8 ms. This 3 dB increase was expected: the same method is used in both cases, but the length of the incoming signal double and
It gives directly the code delay error. For the PLL, the two-quadrant arctangent discriminator has been chosen and is proportional to the phase error:

D = tan 1

Figure 19: Scheme of the Costas loop used to follow the Doppler The other goal of tracking is to follow the code over time using a DLL (Delay Lock Loop). As shown in Figure 20, the incoming signal is multiplied by the local carrier and then by the local replicas of the spreading code. The incoming signal is correlated three times for I and Q with three replica of the code: Prompt : supposed to be aligned with the input signal Early : shifted to the left from the prompt Late : shifted to the right from the prompt After these three correlations, the outputs are integrated and are combined using a discriminator. The discriminator output is passed through a filter (the same idea as for the PLL). The corrections are applied in function to align the prompt channel for the next turn of the loop.
For the filters, a second order filter was originally implemented for both the PLL and DLL. But since a second order loop is sensitive to the range acceleration (to the satellite), a third order PLL has finally been developed. The computation of the C/No is one of the important characteristics to analyze the performances of the tracking. To compute the C/No, the Van Dierendonck (1996) algorithm has been used:
1 NP 1 C = 10 log10 T M NP N0
is the signal lock detector. The value chosen

Figure 22: Doppler using a third order PLL over 30 s All the parameters of the code tracking can be chosen the same as GPS L1 (as described in Kaplan) except the Early-Late spacing. Indeed, due to the BOC modulation, the shape of the Early-Late curve is not the same as with GPS L1 as demonstrated in Figure 23. Indeed, the shape of the Early-Late curve changes the function of the Early Late spacing due to the two sided peaks of the BOC modulation.
Figure 25: Values of the I and Q at the output of the prompt correlator
CONCLUSION AND FUTURE WORK Four acquisition methods and a tracking algorithm have been implemented for the pilot and data channel of Galileo L1 and tested using real data. Due to the rate of change in the data bits/navigation messages, new techniques are needed to acquire these new signals. Beginning with the common zero padding technique, new methods of acquisition have been created. The four methods have been tested using real data from the Galileo test satellite GIOVE-A. These four methods were compared in terms of acquisition sensitivity and processing time. The two methods of acquisition over 16 ms have a higher deflection coefficient (i.e., higher sensitivity) but has to be used only if the signal is too weak to be acquired using 8 ms of incoming signal, due to the processing time. For the tracking, the common methods have been used, the only difference is the EarlyLate spacing which has to be chosen carefully due to the BOC modulation. The results found by the software receiver developed have been checked and validated using the NovAtel 15a receiver. A statistical analysis will soon be performed to compute the probabilities of false alarm and detection, as well as the theoretical time processing for each of the four acquisition methods implemented. The study of a method to combine the pilot and data channel is under investigation. A Kalman filter will be implemented to track and combine the two channels and improve the tracking performances. Then, the GPS L1 C/A signal as well as the future GPS L1C signal will be added to this receiver.
Figure 24: Error in chip computed by the DLL discriminator for an Early Late spacing of 0.1 chip (on the top) and of 0.5 chip (on the bottom) In Figure 25, the data bit are clearly visible in the accumulated I component as expected. Since the sign of the data bit can change each spreading code period, the peaks are sharper than in the case of GPS L1. Almost all the power is in the I component and only a small part in the Q component. The C/No computed using the algorithm described in Van Dierendonck (1996) is 45.7 dB (using a third order PLL). The one found by the NovAtel 15a receiver is 42.3 dB but the parameters of the loop filters may not be the same and the oscillators are different.

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