This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
Since Global Navigation Satellite Systems (GNSS) show degraded performance in dense urban and indoor areas, a positioning sensor based on Digital Video BroadcastTerrestrial (DVBT) systems is presented in this paper. DVBT signals can be considered as signalsofopportunity for positioning, due to their good properties. One of the challenges to overcome is to distinguish the signals from different emitters. Here, we suppose that the user can first compute his position by GNSS during an initialization phase, which is used for solving all the ambiguities concerning DVBT emitters. Starting from there, DVBT signals can be used for aiding positioning when the user enters a GNSSblocked area, up to a limit case, where all the GNSS satellites are not in view and only DVBT signals are used for positioning. We tested this method by simulation, by adopting the Hata model for the emitter attenuations and the Rayleigh model for multipath. The obtained results show good performance if the receiver correctly associates the signal to the user's motion.
Global Navigation Satellite Systems (GNSSs) have been widely used in many applications for positioning, navigation and timing. However, in urban areas and indoor environments, where position information is required for many applications, GNSSs show degraded performance in terms of precision and availability, because of the signal loss or attenuation and multipaths due to obstacles. Fortunately, in these areas, many local networks are deployed, such as 2G, 3G, WiFi, LTE (Long Term Evolution) and DVBT (Digital Video BroadcastTerrestrial). They were originally designed for other purposes, but they can be used for positioning, thanks to their properties, such as a high signaltonoise ratio (SNR).
In this paper, we consider DVBT systems. DVBT is the European digital TV standard. It adopts the Orthogonal Frequency Division Multiplexing (OFDM) technique. Therefore the whole bandwidth is divided into many subcarriers, in which the pilot subcarriers are included. We used these pilot subcarriers to estimate the ranges between the receiver and different emitters with a mechanism similar to the one used by GNSS receivers. Since the SNR requirement for ranging is much lower than the one required by TV service, the receiver is able to see several emitters in one point. If three or more signals are successfully processed, the receiver can provide a DVBT only the positioning; otherwise, it can be used to assist GNSS.
According to the document [
It is interesting to note that some companies transmit the emitter ID within their bit streams, which are then completely equal apart from this small difference (this is done, for example, by Rai in Italy). This causes a (very limited) penalty, but is very useful for network management and control. It is clear that this extrainformation can be very useful also for positioning purposes, since it highly simplifies the association of each echo to the corresponding emitter. Anyway, since the ID emitter transmission is optional in the DVBT standard (which is much more used and available than DVBHandheld (DVBH)), we have not considered it in the study, and we have proposed another way to solve the ambiguity. (Clearly, some actions could be adopted in the future to convince the TV companies to transmit it, to further exploit DVBT for positioning.)
The scenario analyzed in this paper considers a position device (PD) consisting of a hybrid GNSS/DVB receiver, where GNSS is the primary positioning system, and DVBT is used as a backup when the number of GNSS satellites is not sufficient for computing the receiver position. In the first phase (called the initialization phase in the rest of the paper), we suppose that the PD is able to compute its position by using GNSS only. In this phase, the PD keeps sensing the DVBT spectrum in order to identify all the DVBT emitters and computes and tracks the ranges between each emitter and the PD itself. Since the emitter positions are known, the ranges can be used to correctly associate each received signal to the corresponding emitter. Notice that a problem could arise when two or more ranges assume the same value; however, the probability that such an event continuously persists as long as the PD is in open sky is very low and can be neglected. When the PD enters a GNSShostile zone (indoor environment, urban or natural canyon or similar) and the number of visible satellites becomes lower than four, the PD can use the DVBT ranges to integrate them, up to a limit solution, where no satellites are visible and the position is computed by using DVBT data only. This last case obviously represents an extreme situation, which may become very fragile, in the presence of path ambiguities encountered when two ranges become equal. The problem can be quite completely eliminated if some redundancy is available or when auxiliary systems are available (
In the literature, the problem of using DVB signals for pseudorange calculation is addressed in some papers. In [
This paper is organized as follows. Section 2 presents a description of SFN DVBT. Section 3 describes the pseudorange estimation method. Section 4 presents two methods to solve the path ambiguity problem. Section 5 presents the simulation results. The paper ends with the conclusions and a future work description.
According to the DVBT document [
OFDM is a digital multicarrier modulation method. It divides the bandwidth into a large number of closelyspaced subbands. On each subband, a Quadrature Amplitude Modulation (QAM) or Quadrature PhaseShift Keying (QPSK) is used, and all the subband signals are summed together. The symbol rate is the same for each subcarrier and is equal to the subband bandwidth. This way, the subcarriers are orthogonal, and the spectra can overlap without causing InterCarrier Interference (ICI) when the receiver is well synchronized. To avoid InterSymbol Interference (ISI) in multipath fading channels, a guard interval is inserted prior to the OFDM symbol. This interval is used to transmit an exact replica at the end of the OFDM symbol, referred to as CP. This gives the OFDM system an excellent multipath resistance: the receiver can easily avoid the ISI if the multipath timespreading is shorter than the guard interval.
The Fast Fourier Transform (FFT) algorithm can be used to implement the OFDM modulation, and the good efficiency of this algorithm allows a large number of subcarriers in operation. In
Normally, in OFDM modulation, the number of subcarriers,
On the receiver side, the CP has to be removed. To do this, a coarselytimed synchronization is needed to find the starting instant of the OFDM symbol. The synchronization can be achieved, for example, by using the Van de Beek algorithm [
DVBT is a digital broadcasting standard created by the European Telecommunications Standards Institute. For mobile services, another available standard is DVBH (Handheld), derived from DVBT. In this paper, only the DVBT is considered, but the proposed positioning technique can be also used for the DVBH, which is more suitable for mobile users in dynamic scenarios.
The DVBT standard family has adopted the OFDM modulation to provide high data rates along with robustness against multipath. The transmitted signal contains four types of subcarriers, as described hereafter:
In the process of positioning computation, we are interested in the ranges between the receiver and different emitters. These can be obtained by estimating the propagation delay. In DVBT, the propagation delay is mainly related to the FFT size,
These values determine the maximum delay that a DVBT receiver can handle. For example, in the 2 K mode with
As shown in
It is well known that the position of an object capable of measuring the distances between itself and some reference points can be performed by using the trilateration method; this is the technique typically employed in GNSS [
identify a reference frame,
identify the emitter locations, p
measure the ranges,
write and solve the navigation equations.
The implementation of the first and fourth tasks does not present any difference with respect to a classical GNSS receiver; so, it is not described in this paper. The second task is the most challenging, since the signals transmitted by the DVBT emitters do not contain the station identifier; so, the receiver is not able to associate each received signal to a specific station. This is not an issue for TV reception, but it is a problem for positioning. Notice that the emitter identifier is foreseen by the DVBT standard, but its transmission is optional; so, it is ignored in this study. The method proposed in this paper to solve this problem is described in Section 3.1. The third task requires the processing of an OFDM signal to estimate the range; so this has to be redesigned with respect to a GNSS receiver.
The next sections will be devoted to the methods used to implement tasks 2 and 3, while the position computation can be implemented by solving the navigation equations with a classical extended Kalman filter (EKF) technique [
We assume here that in the future, a PD is likely to be equipped with a GNSS sensor as a primary tool and with other sensors able to exploit the nearby signalsofopportunity. This means that the architecture of a PD will include a hybrid receiver, which computes its position with GNSS and resorts to SoSs only when the GNSS satellites are not visible. Moreover, in the case of DVBT towers, it is realistic that the PD has a map of their locations (they are indeed available and easy to find also on the web).
In this scenario, we can suppose that the trilateration with DVBTbased measurements is generally preceded by a phase of position computation based on GNSS, performed when the PD is in open sky with complete visibility of GNSS satellites. This phase is the standard mode of operation and, at the same time, represents the initialization phase for the position computation based on DVBT. During this phase, the PD continuously evaluates the ranges,
Each range can be written at each discretetime instant,
Another benefit of the initialization phase is that the out bound peaks can be discarded, as shown in
In order to obtain a position fix, several ranges are needed in our system. In the case of additive Gaussian noise (AWGN), they can be obtained by the Maximum Likelihood (ML) estimation through correlation. Since the pilot subcarriers are modulated by PRBS, the incoming signals can be correlated with the local generated replicas, similar to the mechanism used by GNSS receivers [
First of all, the PD has to create a local replica of the SPSs, but the locations of the SPSs of two successive OFDM symbols are different, as shown in
It is well known that the ML estimation of the delay of a noisy signal,
In the ideal case of a noisefree channel, each received SPS,
To perform the correlation, a local replica of
In the ideal case of a single emitter in a noisefree channel, without multipath and frequency offset, the correlation,
In order to mitigate the side lobe of the correlation function, we use a windowing technique. By adopting a hamming window, the correlation becomes:
In a scenario with more than one emitter, the correlation is characterized by the presence of several peaks, each one corresponding to a delay,
In our experiments, we have used a mechanism consisting of two stages; the first one, called
The criterion adopted in the acquisition stage is the minimization of the mean squared error between the measured correlation,
The minimization can be done by adopting the Matching Pursuit (MP) algorithm [
Once the coarse delay estimation has been achieved by the acquisition stage, the tracking stage can be used to refine this estimation by using an earlylate delay lock loop (DLL) similar to the one adopted in a GNSS receiver. An example of DLL design can be found in [
Since there is only one sample for each subcarrier, the output of the discriminator will change rapidly once the correlation peak jumps from one delay point to the adjacent one. This is different from the tracking process used in a GPS receiver, where the receiver can track the signal smoothly from one chip to the next one. In order to solve this problem, a reacquisition function is implemented. If the output of the discriminator is above a given threshold, the receiver will enter the reacquisition stage. This stage is similar to the acquisition stage, but the correlation is only calculated upon a small set of delay points, which are centered on the delay obtained from the tracking process. Here, we choose three delay points. In fact, the receiver trajectory is continuous, and then, the correlation peak can only jump from one delay point to one of the adjacent two points (depending on the increase or decrease of the range). If all the correlation results are below a given threshold, the tracking is considered as unlocked. The receiver will restart from the first step. Otherwise, the receiver goes back to the tracking process with the new estimated delay obtained in the reacquisition stage, as shown in
It is well known that the minimum number of reference points for performing the trilateration process in a 3D space is four. In practice, in most applications, three reference points could be enough, as the intersection of three spheres gives two solutions, one of which is not realistic and can be discarded. Moreover, some aiding data can be provided during the initialization phase, such as the synchronism, and the user altitude, further reducing the minimum number of DVBT emitters.
In a more realistic situation, three or two DVBT signals should be sufficient, considering that in most applications, some data can be considered quite constant (
In this section, two methods are presented to solve the path ambiguity problem, which is caused by wrong signal association during the user's motion, which can be observed from
When a user receives two or more DVBT signals with similar or exactly the same propagation delays, it can exploit the visibility of a single GNSS satellite to solve the path ambiguity problem by comparing the ranges. This method is described by considering the case of two DVBT signals with the same propagation delay Therefore, two possible positions are calculated.
In
When the pseudorange comparison method is active, the user can compare
If one of them is above a given threshold, the corresponding position can be marked as fake, and this path will be discarded in the further calculation. We choose three times the standard deviation of the satellite range error as a reasonable threshold, considering that the distance difference corresponding to the correct path will be less than the threshold, with a probability of 99%.
Another method to select the correct path is based on the Doppler effect, due to the relative motion between the satellite and the receiver. The Doppler effect is generally expressed in terms of frequency shift, on the basis of the quantities shown in
During the path ambiguity phase, the receiver can compute a vector containing the coordinates of position and velocity for each path: one of them is correct, and the others are fake. For each possible vector, the receiver can then calculate the corresponding Doppler effect expressed as:
It is known that a GNSS receiver is able to estimate a Doppler shift, Δ
In our application, we assume that the PD is able to receive the signals broadcast by different DVBT emitters belonging to the same SFN. To analyze how the PD can handle these signals, we assume a scenario with
One important aspect for positioning is the Doppler effect. Since all the emitters are fixed, the Doppler effect is introduced by the receiver's motion. In [
The simulation experiments have been done for the scenario shown in
In the scenario of
For the signal generation, we have used the Anritsu MX3700 generator, which is a laboratory Radio Frequency (RF) generator that can be modulated by an array of complex baseband samples. As an option, a DVBT/H sample generation software is sold. We used such software to generate DVBTcompliant baseband signals used as simulation sources. The receiver has a constant speed equal to 100 m/s, while the direction of the velocity changes from timetotime. The signal received along the path has been simulated by combining shifted and attenuated versions of the generated signal. The delays have been simulated by shifting the FFT window according to the corresponding ranges between the user and the emitters. The SNR is simulated according to
Here, we suppose all the DVBT transmitters are placed on the same height at 100 m. Furthermore, since all the emitters use the same frequency, the propagation loss changes only with the distance. The SNR of the received signal has been set equal to 10 dB, where the distance between the user and the emitter is equal to 5 km. The SNR in the other points is calculated according to
The position is computed in two dimensions, regardless of the altitude, every 0.2 s.
In the first experiment, the position is evaluated in the absence of multipath and by ignoring the propagation loss. The idea is to test only the capability of a system based on DVBT, and GNSS is only used in the initialization phase. The simulation length is set to 20 s. The four DVBT emitters are placed in this way: the two emitters (E1 (−1,000,0) and E2 (8,000,0)) placed on the xaxis have quite different distances with respect to the origin of the reference system, while the other two (E3 (0,4,000) and E4 (0,−4,000)) on the yaxis are symmetric with respect to the origin.
The receiver still makes the correct signal association after this point, and the receiver will estimate the trajectory correctly. This is similar to the case of signals from different emitters with significantly different propagation times. In this case, the simulation results show good performance, even in highly dynamic scenarios (e.g., 100 m/s), as shown by the green circles. In our simulation, the receiver achieves a performance with a Root Mean Square (RMS) = 6.8 m, Mean error = 6.0747 m and standard deviation
The receiver makes a wrong signal association after reaching the origin of the reference frame, which means the signal emitted by E3 is associated with E4, and the signal of E4 is considered as coming from E3. In this case, the estimated trajectory deviates from the true one, as shown by the red diamonds.
Since we cannot know the true trajectory in the real cases, some additional information (e.g., the cell ID information, map information for map matching, signals from other system) is needed to determine which trajectory is correct in the case that two or more signals have a similar propagation time. Two methods have been introduced in Section 4.
In this experiment, the Hata model introduced in Section 5 is used. Additionally, the path ambiguity problem has been solved by the methods introduced in Section 4. In order to simulate a large range of SNR, the simulation length is set to 100 s, and the two emitters on the yaxis are located so as to have different distances with respect to the origin.
By multiplying the estimated delay by the speed of light, we obtain the range:
In this simulation, the estimated position can be expressed as:
Several different trajectories have been simulated. The true trajectories and the positioning errors,
In this section, we simulate the Rayleigh channel for multipath, which is suggested by the DVBT standard [
The correlation with the Rayleigh multipath channel is shown in
In this section, we simulate a scenario to test the performance in different SNR. In this scenario, all the received signals have the same SNR, which changes from −10 dB to 10 dB for different simulations. Additionally, the position errors are shown in
In this part, we simulate the scenario in which there is one transmitter unsynchronized. We suppose emitter 1 is unsynchronized with the other three emitters, which are synchronized with GPS time during the position calculation. Different time offsets are tested; while in each simulation, the time offset stays constant. The four trajectories used in Section 5.3 are also simulated here.
In
In this paper, a positioning method based on DVBT Single Frequency Networks has been presented. This method uses the scattered pilot subcarriers of OFDM symbols to measure the Time of Arrival (ToA) of the signals transmitted by the DVBT emitters. In our study, we suppose that the user is equipped with a hybrid GNSSDVBT device. GNSS is used in a first initialization phase to solve the ambiguities referring to the various DVBT emitters. When this phase is completed, the user position can be obtained by using DVBT signals when the user enters a GNSSblocked area. (Note that transmission of the emitter ID would be very useful for positioning. Since it is optional, it has not been considered in the study, but obviously, it would further simplify initialization and tracking of DVB signals.)
The method has been tested by simulation in a dynamic scenario. The simulation results show that a position mean error = 6.0747 m can be achieved if the user can correctly associate the signals to the emitters. If the receiver makes a wrong association, some additional information is needed to determine which trajectory is the correct one. The Hata model has been used to simulate emitters with different SNRs, and a Rayleigh channel has been also introduced to take into account the multipath. The results shows that the range error changes with respect to SNR, while the position estimates do not change significantly along the trajectory. However, if one of the DVBT emitters is unsynchronized, the position error will increase as the time offset increases.
The result of this study is that the structure of the DVBT SFN signals is such that a PD working with DVBT signals can be conceived. At this point, the performance of the positioning algorithms in the presence of different errors sources has to be evaluated. In our future work, a more realistic multipath channel will be considered, and an analysis taking into account other error sources will be performed.
The detection algorithm proposed in [
This algorithm makes use of the signal property that an OFDM symbol has the same scattered pilot subcarriers as the OFDM symbol located four symbols earlier. The correlation of these two OFDM symbols is computed, obtaining:
The maximum value of the four correlations gives the location of the scattered pilot subcarriers of the
The authors declare no conflict of interest.
Orthogonal Frequency Division Multiplexing (OFDM) transmission system.
Digital Video BroadcastTerrestrial (DVBT) pilot organization.
Initialization pahse.
Associating the signals to corresponding receivers.
Scattered pilot location of a quadruplet resulting from combining four consecutive symbols.
The flow diagram of the reacquisition stage.
True and estimated trajectories.
Illustration for pseudorange comparison.
Doppler effect.
Analyzed scenario.
Acquisition results (correlation).
Correlation results in the Hata model.
Pseudorange error for emitter E4.
Different trajectories and the positioning errors.
Acquisition results with multipath channel.
The position estimation errors with multipath channel.
The position errors in different SNR.
The position estimation errors with one transmitter unsynchronized.
DVBT parameters.
2,048 (Mode 2 K)  
4,096 (Mode 4 K)  
8,192(Mode 8 K)  
1/32, 1/16, 1/8, 1/4  
7/64 μs (8 MHz))  
1/8 μs (7 MHz)  
7/48 μs (6 MHz)  
7/40 μs (5 MHz) 
Parameters of DVBT signals. FFT, Fast Fourier Transform; CP, Cyclic Prefix; SNR, signaltonoise ratio.
FFT size 
2,048 
CP length 

Signal bandwidth  8 MHz 
Length of simulation  20 s, 100 s 
Symbol duration 
280 μs 
Sampling period 
109 ns 
SNR  10 dB 