Positioning Using OFDM-based Digital TV: New Algorithms and Tests with Real Signals

Damien Serant, Ecole Nationale de l’Aviation Civile (ENAC) / TéSAOlivier Julien, Christophe Macabiau, ENAC

Lionel Ries, Paul Thevenon, Centre National d’Etudes Spatiales (CNES)Mathieu Dervin, Thales Alenia SpaceMarie-Laure Boucheret, ENSEEIHT

BIOGRAPHY

Damien Serant is a PhD student in the signal processing lab of the Ecole Nationale de l’Aviation Civile (ENAC - French civil aviation university) and working on hybridization of GNSS and OFDM signals. He was graduated as an electronics engineer in 2008, from the ENAC in Toulouse, France.

Olivier Julien is an assistant professor at the signal processing laboratory of ENAC. His research interests are GNSS receiver design, GNSS multipath and interference mitigation and GNSS interoperability. He received his B.Eng in 2001 in digital communications from ENAC and his PhD in 2005 from the Department of Geomatics Engineering of the University of Calgary, Canada.

Christophe Macabiau is graduated as an electronics engineer in 1992 from the ENAC. Since 1994, he has been working on the application of satellite navigation techniques to civil aviation. He received his PhD in 1997 and has been in charge of the signal processing lab of the ENAC since 2000. His research now also applies to vehicular, pedestrian and space applications, and includes advanced GNSS signal processing techniques for acquisition, tracking, interference and multipath mitigation, GNSS integrity, as well as integrated NSS-inertial systems and indoor GNSS techniques.

Lionel Ries has been a navigation expert in the Transmission Technique and signal processing (TT) Department at CNES since June 2000, where he coordinates navigation technical activities. He is responsible for research activities on GNSS2 signals, ground and spaceborne receivers, payloads, and systems. He contributed to the invention of the CBOC signal. He provided support to the 2004 US-EU agreement on GPS and Galileo. He was responsible for the development of the L1-L2C signal processing algorithms now implemented in the ASIC and processor of the TOPSTAR 3000 receiver, in the frame of a CNES R&D activity. He graduated from the Ecole Polytechnique de Bruxelles, at Brussels Free University, and received an M.S. degree from the Ecole Nationale Superieure de l’Aeronautique et de l’Espace (Supaero) in Toulouse.

Paul Thevenon is GNSS engineer in the GNSS signal processing team of CNES (Centre National d'Etudes

Spatiales), the French space research center. He graduated as electronic engineer from Ecole Centrale de Lille in 2004 and obtained in 2007 a research master at ISAE (Institut Supérieur de l'Aéronautique et de l'Espace) in space telecommunications. In 2010, he obtained a PhD degree in the signal processing laboratory of ENAC (Ecole Nationale de l’Aviation Civile) in Toulouse, France by studying the feasibility of self-positioning a receiver using mobile TV signals. His current activity is GNSS signal measurement and processing, with an emphasis on urban environment.

Mathieu Dervin has been with the research department of Thales Alenia Space in Toulouse, France, since 2006. He is carrying out technical studies to prepare the future space telecommunication systems. His research interests cover advanced digital communication techniques applied to the satellite transmissions, and include waveform and receiver architecture design. He received the Eng. degree in 2000 and the Ph.D. degree in Communications in 2005, both from Télécom ParisTech.

Marie-Laure Boucheret received the Eng. degree in Electrical Engineering from ENST Bretagne, Toulouse, France, and the M.Sc. degree in Signal Processing from the University of Rennes, both in June 1985. In june 1997, she received the Ph.D. degree in Communications from TELECOM ParisTech, and the "Habilitation à diriger les recherches" in June 1999 from INPT University of Toulouse. From 1985 to 1986 she has been a research engineer at the French Philips Research Laboratory (LEP). From 1986 to 1991, she has been an engineer at Thales Alenia Space, first as a project Engineer (TELECOM II program) then as a study engineer at the transmission laboratory. From 1991 to 205 she was a Associated professor then a Professor at TELECOM ParisTech. Since March 2005 Marie-Laure Boucheret is a Professor at the National Polytechnic Institute of Toulouse (ENSEEIHT - University of Toulouse). She is also with the Signal and Communication group of the IRIT Laboratory.

ABSTRACT

Indoor and urban positioning is an important market which is foreseen to grow significantly in the future years. Unfortunately, in indoor and urban environment the classical mean of positioning based on Global Navigation

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Satellite Systems (GNSS), has a limited availability and accuracy due difficult multipath conditions and signal blockage by buildings. One alternative that has been explored in the recent years is the use of Signal-of-Opportunities (SoO), such as Wi-Fi, mobile telephony, radio or television signals. Among all SoO available in the air, those based on the popular Orthogonal Frequency Division Multiplexing (OFDM) modulation has been chosen in this work. To demonstrate the potential of OFDM signal for positioning, the work presented on this paper focuses on, as a study case, the European standard for digital TV DVB-T. This paper presents the developed pseudorange estimation method using DVB-T signal. To assess its performance on real signal, a flexible and low-cost test bench has been designed to record and post-process TV signals. The results of two tests on real signals, in two emitters configurations, are finally proposed, showing very good and promising results and demonstrating the potential of OFDM signal to be used as a SoO.

INTRODUCTION

Because of recent regulatory incentives (E911) and development of numerous localization services and applications (mobile positioning, location-based-services, etc…), urban and indoor positioning represents a significant market nowadays. However, it is also known that indoor and urban environments are challenging for Global Navigation Satellite Systems (GNSSs) because of signal blockage, multipath, interference, etc… And even if specific GNSS developments have been done to handle this issues (high-sensitivity, assisted-GNSS, system upgrade), they only provide a limited position availability, accuracy and continuity in challenging environments. Some alternatives exist to complement GNSS in those difficult environments. These include other navigation sensors (e.g inertial sensors, magnetometers, odometers, laser, video), dedicated radio-location systems (pseudolites, RFID, UWB) or signal-of-opportunity (SoO). SoO are communication signals (e.g. mobile telephony, TV, radio, Wi-Fi signals) used opportunely for positioning. Even if they are not meant for positioning, they have the advantage of availability and plurality in urban and indoor environments and permit, by definition, a good integration of the communication and positioning services. A complete analysis on the use of SoO can be found in [1]. Among all the communication signals that could be used as SoO, this article focuses on signals based on the Orthogonal Frequency Division Multiplexing (OFDM) modulation, which appears to be a good candidate to provide a positioning service considering the increasing interest of this modulation for communication and broadcasting for actual and future signals (Wi-Fi, WiMAX, LTE, DVB-T/H/SH, DAB, T-DMB, ISDB-T, MediaFLO…). In the variety of OFDM-based standards, the European standard for digital television, the Digital

Video Broadcasting – Terrestrial (DVB-T) standard, has been chosen as a study case to develop a pseudorange (PR) estimation method and perform test on real signals. This article aims at showing real signal tests based on ranging methods previously developed by the authors. Although the ranging method presented in this article has been developed for DVB-T, it is applicable to other OFDM-based signals. This work complements previous studies on the feasibility of OFDM-based positioning, by showing results based a dedicated test bench using real signals collected in the targeted environment. Indeed, previous work focused on the proposition of OFDM-based tracking algorithm adapted to a terrestrial network of emitters [2] at investigating its theoretical performance [3], and to provide first assessments based upon semi-simulated data [4].

This article is organized as follows: The first section introduces the principle of the OFDM modulation and presents the DVB-T standard. The second section presents the basic principle of the developed PR estimation method using DVB-T signal. The third section describes the designed test bench and its functioning. The fourth section presents the results of a test on real signal in two DVB-T emitter configurations: one DVB-T emitter synchronized on GPS time and two DVB-T emitter in SFN.

OFDM MODULATION AND DVB-T STANDARD OVERVIEW

Orthogonal Frequency Division Multiplexing The concept of OFDM [5] consists in transmitting in parallel complex data symbols over orthogonal narrowband subcarriers (1 subcarrier carries 1 symbol). The width of these subcarriers is chosen narrow enough so that the channel frequency response can be considered as flat over the subcarrier bandwidth. The consequence is that channel equalization becomes very simple even in case of dense multipath environment. Thanks to the orthogonality of the subcarriers, their spectra can overlap without interfering with each other, allowing an excellent spectral efficiency and no Inter-Carrier Interference (ICI) when the receiver is synchronized. An OFDM useful symbol is obtained by passing the complex data symbols through an inverse-Fast Fourier Transform (iFFT) operator. The useful part of the OFDM symbol is thus composed of samples. To take advantage of the FFT algorithm, is generally chosen to be a power of two. Conversely, the demodulation of an OFDM symbols is performed by a direct FFT. Additionally, as illustrated on Fig. 1, a guard interval of

samples is inserted before the useful OFDM symbols in order to avoid Inter-Symbol Interference (ISI). In many cases, this guard interval is a replica of the last

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samples of the OFDM symbol, and is referred to as Cyclic Prefix (CP). By doing so, any demodulation of the OFDM symbol that is done with an N-sample FFT starting in the CP will only result in a phase rotation of each subcarrier proportional to its frequency offset, thus easily equalized. This also means that only a rough synchronization is necessary to demodulate the received signal. An OFDM symbol (useful symbol + CP) is thus composed of

samples. Fig. 2 represents a typical OFDM modulator and demodulator.

The received samples are affected by multiple impairments: multipath channel distortion, timing offset (TO) due to propagation delay, carrier frequency and sampling clock offsets (CFO and SCO) due to the difference between the local oscillator and sampling clock of the emitter and the receiver [6]. A synchronization and correction module thus needs to be present in the receiver to estimate and correct for the TO, CFO, SCO and multipath channel effect. Examples of these techniques can be found in [6], [7] or [8]. Thanks to the periodicity introduced by the CP (see Fig. 1), the timing synchronization does not have to be very precise to be able to demodulate the data. Indeed, if the FFT window in the demodulator starts in the CP, it will only result in a phase offset that can be easily corrected during the equalization process. Indeed, a subset of the sub-carriers generally carries pilot symbols, which value and position are known by the receiver, that can be used to assess the channel distortion over the frequencies.

The specific reasons to explore the OFDM modulation capability for positioning are multiple:

OFDM modulation has been chosen by a large number of modern telecommunication and audio/video broadcast standards (Wi-Fi, WiMAX, DAB, T-DMB, DVB-T/H/SH, ISDB-T, LTE…). This preeminence of OFDM-based signals makes them evident candidates to be used as signal-of-opportunity for ranging applications, and good candidates for nav/com services. OFDM timing and frequency acquisition is very simple and quick thanks to the presence of the CP. OFDM signal includes pilot symbols that allow computing correlations between the received

signal and a receiver-generated local replica, thus creating the grounds for precise synchronization (as in GNSS). The OFDM can be used in Single-Frequency Networks (SFNs). A SFN is a network where all the emitters send the same signal at the same frequency in a synchronized way (usually based on GPS time and frequency). A SFN can be very useful to extend the coverage of an emitter to isolated/masked areas without requiring additional frequency. From a positioning point of view, a SFN is also extremely interesting because it allows tracking multiple signals coming from several synchronized emitters on the same frequency (only 1 tuner required). This synchronization of the emitters means that the monitoring of the emitter clock drift might not be needed. Examples of techniques to use SFN for positioning can be found in [2].

Digital Video Broadcasting – Terrestrial (DVB-T) Standard The DVB-T [9] is a European standard, used worldwide (see Fig. 3), and based on an OFDM air-interface for digital TV broadcasting to fixed receivers in the VHF and UHF bands. This standard defines a family of OFDM signals which depends on three parameters:

the number of subcarriers or the FFT size ( ), the ratio between the Cyclic Prefix length and the useful OFDM symbol length ( ),which provides flexibility according to the expected multipath delay, and the sampling period ( ), which controls the bandwidth of the DVB-T signal.

Table 1 shows different possible values defined in the DVB-T standard for each parameters.

Figure 1: Cyclic prefix illustration

Figure 2:OFDM modulator (top) and demodulator (bottom)

Figure 3: Countries that have deployed or adopted DVB-T and its evolution DVB-T2 [10]

OFDM symbol k OFDM symbol k+1CPCP

samples samples

Modulator

Symbolmapping Serial to

Parallel IFFT Parallelto Serial

Tx bitsTx

samplesAdd CP

Demodulator

Serial toParallel FFT Parallel

to Serial

Rxsamples

Rx bitsRemove

CP

Symboldemapping

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Parameters Possible values2048 (Mode 2K), 4096 (Mode 4K) and

8192 (Mode 8K)1/32, 1/16, 1/8, 1/4

7/64 s (8 MHz channels), 1/8 s (7MHz), 7/48 s (6 MHz) and 7/40 μs (5

MHz)

The subcarriers of the useful OFDM symbol carry different kind of information:

Null subcarriers which are located on the edges of the signal spectrum and have a zero value. They serve as guard bands to avoid out-of-band emissions of the OFDM signal. Data subcarriers which are QAM-modulated (QPSK, 16-QAM and 64-QAM are possible) and have their amplitude normalized in such a way that their variance is unitary. Transmission Parameter Signaling (TPS) subcarriers which are BPSK-modulated and carry information about the actual transmission parameters. Pilot subcarriers which are BPSK-modulated. Their value is given by a known Pseudo-Random Binary Sequence (PRBS). Their amplitude is boosted by a factor of 4/3 compared to Data and TPS subcarriers.

The pilot subcarriers can be of two types: continuous pilots and scattered pilots. Continuous pilots are always located on the same subcarriers on every OFDM symbols. On the contrary scattered pilots are inserted every 12 subcarriers and the first pilot subcarrier index takes four different values (3, 6, 9 or 12) depending on the OFDM symbol number. Therefore the scattered pilot pattern repeats every 4 OFDM symbols. This organization is illustrated in Fig. 4 where only non-null subcarriers are represented.

As it was stated in introduction, the investigation of ranging techniques using the DVB-T standard has its origin in the desire to assess the capability and feasibility of OFDM-based positioning system. Even if it is not the best candidate for an autonomous operational system (particularly it generally has a low emitter density), it can be seen as a potential complement to GNSS-based positioning (DVB-T emitters are in some cases

synchronized with GPS time). It is also particularly adapted for testing OFDM-based ranging:

The signal definition is very simple (no specific pilot OFDM symbols, classic pilot grid) which makes the reuse of this work possible for other OFDM-based standard. It is already deployed and operational (in France and many other countries) which allows tests on real signals, necessary to assess the performance of the ranging technique. Both Multi-Frequency Networks (MFN) and Single-Frequency-Network (SFN) are available, thus permitting to test two ranging solutions. It is a wide-band signal (5 to 8 MHz) that could offer promising synchronization capabilities.

Compared to GNSS, it has to be kept in mind that DVB-T is a terrestrial communication system. In terrestrial networks, the direct signal comes from emitters that are often close to the horizon. Consequently, the direct signal (mandatory for accurate ranging based on propagation time measurements) might be blocked, and multipaths can be numerous and powerful, especially in urban areas. It even often occurs that multipaths are more powerful than the direct signal. This is for instance taken into account in the power delay profile of the propagation channel used in the DVB-T standard to assess the demodulation performance [9]. These numerous multipaths are not a problem for the signal demodulation thanks to the simple and efficient OFDM channel equalization achieved with the pilot sub-carriers, as long as the maximum multipath delay remains lower than the CP duration to avoid ISI. On the other hand, for positioning application based on timing measurements, these numerous multipaths are a problem that has to be specifically handled.

BASIC PRINCIPLE OF THE PR ESTIMATION METHOD USING DVB-T SIGNALS The proposed DVB-T ranging method was presented in [11]. More details on the technique can be found in [12], [3], [13], or [4]. It is based on the computation of a classical correlation between the received signal and a local replica. This correlation is used during the acquisition and tracking phases. The local replica used to compute the correlation function is composed of the pilot sub-carriers only (the other subcarriers, a priori unknown by the receiver, are set to zero). It can be easily shown that the resulting correlation function is a sinc function (see its absolute value on Fig. 5) [11]. The width of the correlation peak is approximately 2.4 sample periods or equivalently 80 meters for 8 Mhz channels, 90 meters for 7 Mhz channels, 105 meters for 6 Mhz channels and 130 meters for 5 Mhz channels.

Table 1: Possible DVB-T signal parameters

Figure 4: DVB-T pilot organization

Frequency (subcarriers index)

Tim

e (O

FDM

sym

bols

)

Continuous pilotsScattered pilotsData & TPS

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Due to the specificities of the terrestrial propagation channel already discussed, the correlation function obtained from real signals will present multiple peaks corresponding to all the replicas of the transmitted signal reaching the receiver. These peaks can evolve very fast (e.g. fading) due to the changing environment in urban conditions. More notably, the peak corresponding to the first received signal (the one of interest for ranging) is not necessarily the most powerful and might not even be present. In order to try to always track the first signal (either the direct signal, or by default one of the shortest replicas), the proposed ranging method uses multiple delay lock loops (DLL) in order to constantly track several correlation peaks. This allows relying on the second tracked shortest replica if the first one disappears due to fading or signal blockage. The following method is then used (although slight variations are used depending if the emitters are in SFN or not):

First, an iterative algorithm, that could be the Matching Pursuit [14] or ESPRIT [15], is used to acquire the delays corresponding to the different peaks of the correlation function. In order to make sure that the direct signal or the shortest detectable replica is not missed, this acquisition is run periodically. Second, all (or a subset of all) the acquired peaks are tracked independently using several classical DLL using a normalized early-minus-late-power (EMLP) discriminator [16]. The shortest tracked delay is then used to form the pseudorange measurement. Specific detectors are used to minimize the number of replicas tracked.

Note that the correlation function shown in Fig. 5 presents significant side-lobes, which can lead to significant impairments due to near-far effect, in particular in SFNs. To mitigate this, it is possible to use windowing techniques in order to reduce the correlation side-lobes, as tested in [4].

DESCRIPTION OF THE DEVELOPPED TEST BENCHThe developed test bench, presented on Fig. 6 is composed of three part:

Two TV signal recording devices, made with the USRP2 equipped with the WBX daughterboards (see [17] for more information about this equipment), that permit to down-convert and digitize the TV signal at the local oscillator and sampling clock frequencies, on two reception chains (one is optional). A GPS receiver, which provided a reference position and supply the GPS time to the two USRP2. A PC, to control the two USRP2 and the GPS receiver. It retrieves the digitized samples from the 2 USRP2/WBX and the GPS position from the GPS receiver to record them on the hard drive for post-processing.

This test bench is very flexible, thanks to the following characteristics of the USRP2/WBX device:

Tunable LO frequency from 50 Mhz to 2.2 GHz. Tunable sampling frequency from 0.2 to 25 MS/s (Mega Samples per second). Tunable amplifier gain from 0 to 30 dB. Possibility to have 2 synchronized URSP2. Possibility to lock the master clock of the USRP2 on a 10 MHz external reference (typically coming from a GPS receiver or a GPS disciplined oscillator) Possibility to tag the received samples with GPS time thanks to a 1PPS input.

Thus, this test bench, even if it is used in this work to record DVB-T signal, can be used to record any signal in the 50 Mhz to 2.2 GHz frequency band (other bands are possible using other daughterboards). In addition, thanks to the presence of two synchronized reception chains, the following test configuration are possible:

Two mobile TV antennas receiving the same signal to exploit antenna diversity and improve measurement quality. Two mobile TV antennas receiving two signals at different frequencies from the same emitter to exploit frequency diversity. Two mobile TV antennas receiving two signals at different frequencies from two emitters to have two PR measurements. One fixed antenna and one mobile to perform differential measurements.

Figure 5: Absolute correlation function

Figure 6: Architecture of the test bench

UHF Antenna

USRP2/WBX Master

L1/L2 AntennaGPS receiver

Novatel OEM4

To PC for sample recording

10MHz ref. and 1PPS

To PC for position recording

Gigabit Ethernet

COM

UHF Antenna

USRP2/WBX Slave

MIMO cable

Optional

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RESULTS OF TESTS ON REAL SIGNAL The DVB-T parameters used in France, where the real signal tests were done are specified in Table 6.

Mode – FFT size 8K - 8192 Approximate bandwidth –

Sampling period 8Mhz – 7/64 μs

CP ratio 1/8 Data symbols constellation 64-QAM

Frequency band 474 Mhz - 826 Mhz

Case of one DVB-T emitter synchronized on GPS time

This test used a DVB-T emitter synchronized to GPS time with a precision of about 30 nanoseconds (not so good but sufficient for our application). The position of its emitting antenna is known with a precision of about 1 meter. Even if this emitter is synchronized on GPS time, it is not phase-locked on it. Indeed. the time of emission of an OFDM symbol does not match an integer millisecond of GPS time contrary to the GPS system in which each start of the spreading code coincides with a new millisecond of the GPS time. Thus, in order to obtain absolute pseudorange measurement and since only one emitter is available (not enough to solve this unknown phase offset), the instant of the OFDM symbols emission have been determined empirically. 10 recordings of 5 seconds of TV signal coming from this emitter have been done, at a know location in direct sight of the emitter and on the top of a hill to avoid multipath error. Knowing the GPS time of the first recorded sample (thanks a functionality of the test bench) and the position of the receiver and according to the delay estimated by the tracking algorithm it is possible to determine the GPS time of the OFDM symbol emission for each recorded signal. To be compared, the values of the GPS time of the OFDM symbol emission is given modulo the OFDM symbol duration (see Table 3).

Test #

GPS time of the first recoded sample (in

seconds in the GPS week)

Estimated delay (in sample)

Computed value of OFDM symbol

instant of emission modulo the OFDM symbol length (in

sample period) 1 483282.6931 8387.02 7223.16 2 483313.8768 6286.70 7223.14 3 483341.3489 5598.41 7222.94 4 483369.8736 2767.25 7223.33 5 483400.3016 7225.57 7223.22 6 483423.5580 8744.17 7223.19 7 483449.3864 5189.99 7223.20 8 483474.5029 3153.34 7223.22 9 483497.6707 4151.88 7223.18

10 483520.8707 5320.90 7223.19

The measured GPS times of the OFDM symbol emission modulo the OFDM symbol duration are close and their mean value is 7223.18 samples with standard deviation of 0.1 sample (3 meters). This mean value, called reference delay, is used in the following test to “transform” the estimated delay into an absolute pseudorange.

Five tests in urban environment with the test bench mounted in a car have been done but only one is detailed here (all provide similar results). In this test, 5 minutes of signal were recorded from two reception antennas spaced by about 1 meter. The trajectory followed by the car during this test is shown on Fig. 7. It includes three static phases (between 0 and 10 seconds, between 70 and 110 seconds and between 285 and 300 seconds). During the remaining time, the car speed is between 0 and 50 km/h. In this tests the integration time is 1 OFDM symbol (about 1 ms) and the loop bandwidth is 1 Hz.

Fig. 8 represents the evolution of the absolute value of the correlation function over time. It can been seen as an estimate of the channel impulse response over time. The color scale represents the relative amplitude of the absolute value of the correlation function in decibel, 0 dB being the maximum amplitude over the whole image. This figure is interesting because it outlines the different characteristics of the channel: presence of many multipath, fading, etc... It also underlines that throughout the test, the direct signal or a short replica of it are present and dominant. This figure also shows that during the statics phases the channel is quite stable.

Table 2: DVB-T parameters in France

Table 3: Determination of the OFDM symbol emission time

Figure 7: Car trajectory during the test

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Fig. 9 shows the estimated pseudorange for each TV antennas compared to the reference PR computed from the GPS-based car position and the known emitter location and Fig. 10 shows the pseudorange error for each antenna. It can be seen that the error is mostly positive, which is a clear observation of non-line-of-sight (NLOS) error. This error appears when the direct signal is blocked or weak, causing the tracking loop convergence to a multipath peak. In addition, it can be seen that the error associated with each antenna are very different (up to 150 meters) even if they are close (separated only by one meter).

The pseudorange error statistics (mean and standard deviation) are shown in Table 4 for both static and dynamic phases. During the static phases, the PR error standard deviation is very small (about 5 meters for the two antennas) because the channel does not change. However, the mean value of the PR error is very important during the static phases and is very different between the two antennas. During the dynamic phases, the statistics for the two antenna are quite similar. The PR error standard deviation (about 23 meters) is higher than in the static phases due to the quick variations of the channel.

Antenna #1 Antenna #2 Static phase

Dynamic phase

Staticphase

Dynamic phase

PR error mean 55 m 30 m 25 m 24 m

PR error standard deviation

5.4 m 24 m 4.9 m 22 m

An advanced measurement processing technique has been developed to mitigate the NLOS error. As shown on Table 5, when this technique is used, the mean and standard deviation values are significantly reduced, especially during dynamic phases.

Static phase Dynamic phase

PR error mean 16 m 0.9 m

PR error standard deviation 3.5 m 7.3 m

This results are very good and promising and can be seen as an upper bound of the actual performance, since a part of the PR error is due to imperfect GPS time provided by the GPS receiver.

Figure 8: Correlation image

Figure 9: Estimated PR compared to reference PR

Figure 10: PR error for the two antennas

Table 4: PR error statistics

Table 5: PR error statistics with the advanced measurementsprocessing technique

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Case of two DVB-T emitters in SFN This experiment uses two DVB-T emitters in a Single-Frequency Network (SFN). In this particular case, the second emitter (referred as Emitter #2 in the following) is a simple analog repeater of a principal emitter (referred as Emitter #1 in the following), used to fill a hole in the coverage of Emitter #1. Nevertheless it can be considered that these two emitters are in a SFN. Since the two emitters transmit the same signal, the correlation function computed in the receiver presents one peak for each emitter. Thus, the correlation function presented in Fig. 11, obtained at a known fix location, presents two main peaks. The shortest one (around a correlation delay of -100 samples), corresponds to the signal of Emitter #1 and the second (around a correlation delay of 70 samples) to the signal of Emitter #2. The other smaller visible peaks (between the correlation delays 150 and 200 samples) corresponds to multipathes of Emitter #2.

Fig. 12 shows the result of the tracking of this two correlation peaks. In this plot the mean value of each estimated delay has been removed in order to have a better look on the estimated delay variations. This figure shows that the two emitters are not synchronized on GPS time (since the estimated delays are not null) and that, as expected, the two emitters share the same clock (since the estimated delay for each emitter are identical). Thus, it is possible to compute the difference of the estimated delay of each emitter, also known as the time-difference-of-arrival (TDOA), to obtain-clock error-free measurements. If the clock variation can be totally removed using the TDOA operation it remains an unknown bias between the estimated delay of the two emitters. In the case of Fig. 12 the difference between the two estimated delay is about 5505 meters which do not correspond to any geometrical delay between Emitter #1 and Emitter #2. This means that there is unknown delay introduced at the emission of Emitter #2 when repeating the signal of Emitter #1. Unfortunately, this unknown delay could not be determined empirically (no place where in direct sight of Emitter #1 and Emitter #2 and in a open area were found). Thus in order to compare the measured TDOA with the

reference TDOA, this unknown bias is systematically cancelled (the mean values of the TDOA metrics are removed).

Two tests were conducted in this SFN using the test bench mounted in a car : the first in sub-urban area and the second in a urban area (see car trajectories on Fig. 13). The GPS reference trajectory of the urban test is sometimes poor (standard deviation of several meters) due to difficult GPS reception conditions. For the two tests, the static phases are too short to study them independently as in the previous test. In this tests the integration time is one OFDM symbol (about 1 ms) and the loop bandwidth is 0.5 Hz.

Fig. 14 and Fig. 15 shows a close-up of the correlation peaks of Emitter #1 and Emitter #2 in the correlation image of the sub-urban test and of the urban test. In both tests the peak of Emitter #1 is the weakest and it is sometimes difficult to distinguish it in the correlation image, especially in the urban test. It is also clearly visible

Figure 11: Correlation function – Fix location

Figure 12: Estimated delay for each emitter – Fix location

Figure 13: Trajectories of the sub-urban (up) and urban (down) tests

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that in the urban test there is much more multipathes than in the sub-urban test.

In the two tests the TDOA measurements are compared to the reference TDOA computed thanks to recorded GPS position of the car and the known positions of the two emitters. Thus, Fig. 16 and Fig. 17 show the TDOA error for each test. As expected the TDOA error in the sub-urban test is smaller than in the urban test because of less intense multipath condition. For the urban test, the TDOA error is limited even if, according to Fig. 15 the signal of Emitter #1 is very weak. Indeed the small loop bandwidth (0.5 Hz) helps the loop not to diverge when the signal is too weak, to continue the tracking when the signal re-appears.

Finally, Table 6 shows the TDOA error standard deviation for the two tests. The mean value, null by construction, is not presented. Results are again very good and promising, and in this test, thanks to the formation of TDOA measurement, it is sure that the TDOA errors are totally clock-error-free. However, since the mean value of the TDOA error is null by construction it is not possible to conclude on the presence or the absence of bias in the TDOA measurement.

Sub-urban test Urban test TDOA error

standard deviation

5.2 m 16 m

CONCLUSIONS AND PERSPECTIVES A method that permits to compute PR measurement from a DVB-T signal has been presented. The performance of this method has been assessed in real signal tests, in two emitter configurations. For that purpose, a flexible test bench capable of record signal from two synchronized reception chains has been designed. In the first configuration, the DVB-T emitter is synchronized on GPS time and clock-error free PR

Figure 14: Correlation image – Close-up on Emitter #1 (down) and Emitter #2 (up) peaks – Sub-urban test

Figure 15: Correlation image – Close-up on Emitter #1 (down) and Emitter #2 (up) peaks – Urban test

Figure 16: TDOA error for sub-urban test

Figure 17: TDOA error for urban test

Table 6: TDOA error standard deviation

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measurements are obtained. The PR estimation method obtains good performances even if an important positive bias due to NLOS error exist. This bias can be significantly reduced using a advanced measurement processing technique. In the second configuration, two DVB-T emitters in SFN and not synchronized on GPS time are used. By forming TDOA measurement the clock error is totally removed. Two test has been done in sub-urban and urban areas and the results in the two tests are very good and promising, even if the test conditions do not permit to conclude on the presence or the absence of bias in the TDOA measurement. Finally this work proves the feasibility of a positioning system based on PR measurement, with a signal-of-opportunity using the OFDM modulation.

To continue this work one possibility could be to apply the PR measurement method to another OFDM-based signal, more adapted than DVB-T to an autonomous positioning application. Indeed, a DVB-T system has often a weak density of emitter and is often not dimensioned for a mobile and indoor reception. An interesting candidate could be 3-GPP Long-Term-evolution (LTE) (a 4-th generation wireless communication standard based on the OFDM modulation) which targets indoor and mobile reception, has a high density of emitters and, in addition, has a larger bandwidth than DVB-T (up to 20 Mhz for the downlink). Another continuation of this work could be to study the hybridization of the OFDM pseudoranges with GNSS pseudoranges, through, for example, a vectorized DLL.

ACKNOWLEDGMENTS The authors would like to thank the French Space Agency CNES and Thales Alenia Space for funding this work.

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