=Paper= {{Paper |id=Vol-2626/paper13 |storemode=property |title=A Study on Robust Navigation by Means of GNSS, Network LTE and INS Integration |pdfUrl=https://ceur-ws.org/Vol-2626/paper13.pdf |volume=Vol-2626 |authors=Davide Imparato,Jean-Jacques Floch,Elena Simona Lohan,Martin Ruzicka,Petr Casek,Marketa Palenska |dblpUrl=https://dblp.org/rec/conf/icl-gnss/ImparatoFRCP20 }} ==A Study on Robust Navigation by Means of GNSS, Network LTE and INS Integration== https://ceur-ws.org/Vol-2626/paper13.pdf

A Study on Robust Navigation by Means of GNSS, Network LTE
and INS Integration
Davide Imparatoa, Jean-Jacques Flocha, Elena Simona Lohanb, Martin Růžičkac, Petr Casekd
and Marketa Palenskad
a
Airbus Defence and Space GmbH, Munich, Germany
b
Tampere University, Tampere, Finland
c
Evektor, spol. s r.o., Brno-Slatina, Czech Republic
d
Honeywell, spol. s r.o., Brno-Slatina, Czech Republic

Abstract
This paper summarizes the results of the exploratory research work performed by Airbus
Defence and Space (ADS) in the context of the EMPHASIS project (EMPowering
Heterogenuous Aviation through cellular SIgnalS), which aimed at developing innovative
technologies to increase safety, reliability, and interoperability of General
Aviation/Rotorcrafts (GA/R) operations. ADS contribution focused on the development and
implementation of signal processing and navigation algorithms for real-time network-based
radio aircraft positioning and tracking – specifically, real-time joint wireless-network and
GNSS based positioning approaches aided by Inertial Navigation Systems (INS). This
activity was an opportunity for ADS to upgrade its company-own end-to-end navigation
simulator tool “PIPE”, in order to be able to process wireless positioning signals and perform
hybrid GNSS-network LTE navigation. Results obtained from simulations of integrated
GNSS, network LTE and INS navigation in representative urban scenarios are presented. It is
shown that positioning accuracy below 5m can be obtained in difficult scenarios with poor
satellite visibility if GNSS is integrated with LTE and INS.

Keywords
Hybrid GNSS, LTE, INS, GA/R, sensor fusion, robust navigation, positioning, PNT,
filterbank, RAIM.

1. Introduction
The project EMPHASIS (EMPowering Heterogenuous Aviation through cellular SIgnalS) was
funded by the SESAR Joint Undertaking (SJU) and run over two years (throughout 2018 and 2019)
within a consortium of 4 companies and institutions led by Honeywell and including Evektor,
Tampere University of Technology and Airbus Defence and Space (ADS). The key objective of the
project was to develop innovative technology to increase safety and reliability of General
Aviation/Rotorcrafts (GA/R) operations, and their interoperability with both commercial aviation and
emerging drones operations. These aspects are foreseen as critical to secure and improve airspace
access for GA/R users in future airspace environment and increase the safety of their operations. This
objective was addressed by exploring affordable CNS capabilities tailored for GA/R users, focusing in
particular on the use of telecommunication infrastructure and mobile networks for data-link and
positioning, low power ADS-B concept, obstacle/terrain hazards detection, and possible alternative
certification approaches. Results of the different work packages and general information on project
and consortium can be found in [1-3].

________________________
ICL-GNSS 2020 WiP Proceedings, June 02–04, 2020, Tampere, Finland
EMAIL davide.imparato@airbus.com (D. Imparato); jean-jacques.floch@airbus.com (J.J. Floch); elena-simona.lohan@tuni.fi (E.S. Lohan)
© 2020 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR Workshop Proceedings (CEUR-WS.org) Proceedings
ADS work focused on the development of network based navigation techniques and their
integration with GNSS to maximize navigation performance for GA/R applications, in particular in
terms of availability and integrity in challenging (urban and sub-urban) scenarios. Assessment of
GNSS-only positioning accuracy and availability for flying vehicles in a multi-GNSS scenario was
performed in ADS through simulations and measurement results from an urban mobile campaign,
confirming the weaknesses of GNSS-only navigation. Following, ADS activities proceeded with: an
analysis and discussion of wireless communication channel models and algorithms for generating
radio channel simulations; a review of viable strategies of INS/GNSS fusion, to aid GNSS navigation
in sub-urban and urban environments; an assessment of the existing network based positioning
algorithms; and a study on viable methods to monitor the integrity, quantify the integrity risk and
maximize the robustness of navigation. GNSS weaknesses in urban and sub-urban environments, even
when using precise multi-GSNS multi-frequency carrier-phase based techniques (PPP, PPP-RTK), are
well known in the scientific community [4,5]. Similarly, positioning in the 4G and 5G era is topic of
an extensive literature (see e.g. [6-11]), which has been extensively reviewed in the frame of
EMPHASIS project. An overview of the INS system and of the different INS/GNSS coupling
strategies is provided in [12], whereas robust filtering techniques and integrity monitoring methods, of
paramount importance for navigation in aviation and overall for Safety of Life (SoL) applications, are
presented for instance in [13,14].
In the framework of this project, ADS had the opportunity to upgrade its in-house developed
simulation tool “PIPE”, dedicated to GNSS navigation, to be able to generate 4G signals, process
them and integrate the ranging information into INS and 4G-aided PVT. After upgrading of the
simulator software, analyses were run in simulated challenging navigation scenarios, e.g. with
occurrence of anomalies and presence of external attacks (spoofing), to assess the navigation and the
integrity monitoring performance of the chosen robust GNSS+INS+4G navigation algorithm.
The paper is organized as follows: in section 2 the integrated navigation solutions proposed by
ADS are discussed. First the network-based navigation concepts and methods studied and
implemented by ADS are described, next INS and integrated GNSS/INS navigation are discussed and
finally hybrid GNSS, INS and network LTE navigation algorithms and software implementation are
described. In section 3 the simulations set-up and results are discussed. Conclusions are given in
section 4.

2. Integrated Navigation Solutions
2.1. Network-based Navigation
After reviewing different existing network-based positioning techniques, the Time Difference of
Arrival TDoA was the preferred choice for software implementation, since it is the most promising in
terms of achievable positioning accuracy. Such technique, which was the downlink positioning
procedure foreseen in the LTE specification Release 9 [15], uses the difference in the arrival times of
downlink radio signals from multiple base stations (BS) to compute the user position. The LTE
technology included new positioning methods in later specification releases, of which still the most
promising methods, in terms of expected horizontal accuracy, are those based on ranging
measurements, e.g. Assisted GNSS (A-GNSS) and TDoA. Only A-GNSS has so far been successful,
as all the other methods require additional infrastructure or mobile device modifications, which have
limited their deployment. However, ranging-based localization is foreseen to be a fundamental
functionality for future high positioning accuracy applications in 5G. Determining the achievable
localization accuracy in LTE can provide an indication (or better a lower bound) for the performance
of future 5G networks’ localization services.
The PRS signals PSD and CCF were modeled and simulated in a Matlab software implementation,
and lower bounds on the range accuracy obtainable were obtained by means of Cramer-Rao bound
approximation. Figure 1 shows PSD and CCF results obtained for PRSs simulated on Matlab
software, Figure 2 shows the Cramer-Rao bound for two different bandwidths (~1 and 10 MHz).
However, these results can be representative of the actual ranging performance of LTE signals
only in ideal conditions of Line of Sight (LoS) signal reception, with no errors coming from the
propagation in the medium others than space losses. In urban environments, although the TDoA
method is still the most accurate cellular-based location method in LTE, its position accuracy is
mainly limited due to dense multipath. Experimental field measurements in [6] already show the
effects of harsh environment on the positioning. There are two main and complementary strategies for
multipath mitigation: based on the position calculation, and based on time-delay estimation (TDE).

Figure 1 - PSD (left) and CCF (right) of a LTE PRS signal of ~1MHz bandwidth (Matlab simulation).

These methods are presented in detail in [7,8].
Multipath is the major source of ranging bias in urban environments, due to the blockage of the
LoS signal. Figure 3 shows the expected range accuracy of 4G PRS signals as estimated in [7], for
different multipath models and tracking methods, and for different signal bandwidth. Only at the
largest bandwidths the range accuracy is better than 10m. An equivalent multipath error model was
introduced in ADS scenario simulator within the company own software PIPE (discussed in next
section).

EL=0.005 Chip, , ms

Figure 2 - Cramer-Rao bound for LTE PRS signals, with 1 MHz (dashed line) and 10 MHz bandwidth.
Figure 3 - Expected range accuracy of 4G PRS signals as estimated in [7], for different multipath
models (top, EPA channel model, bottom, ETU) and tracking methods (in different colors), and for
different signal bandwidth

2.2. Inertial Navigation
INS/GNSS fusion can provide aid to GNSS navigation in sub-urban and urban environments,
where satellite visibility is obstructed and multipath/NLOS errors are prevalent. INS/GNSS fusion is
particularly helpful in enhancing the integrity of the navigation solution, as the INS provides
redundancy of measurements in all navigation scenarios, it cannot be spoofed (differently from
GNSS), complementing GNSS in most aspects (especially in bridging outages). Among the different
INS/GNSS fusion implementation strategies, the tight-coupling scheme was deemed the most suitable
for a reasonably low-cost solution for commercial drones. Main reasons are that it allows to use
GNSS observations to aid positioning also when less than 4 satellites are visible, it allows the
implementation of filter-bank integrity monitoring techniques, which guarantee integrity in case of
Slow Growing Errors (SGEs), and it is a solution commercially available, at reasonably low costs.
INS limitation lies in the fact that it can only bridge GNSS outages for a limited amount of time. INS
only positioning accuracy in fact diverges rapidly with time, and when using low-cost IMU the
positioning error in absence of GNSS observations, or in presence of only few of them, can grow over
1m in few tens of seconds. As a result, an external aiding – for instance, from the cellular network –
will be necessary, at least in some specific areas of operation.

2.3. Robust positioning and integrity monitoring
Among the Integrity Monitoring (IM) algorithms reviewed during the EMPHASIS activities, an
eRAIM approach [13] and a filterbank approach [14], based on adaptive filtering, were chosen for
software implementation. The second is relatively heavy computationally, but is also the most robust
against anomalies affecting the system. PPP/PPP-RTK techniques (carrier phase based positioning)
were also reviewed within the scope of the project, as they represent absolute precise positioning
techniques that do not require extra infrastructure (close-by reference stations/network). The
advantage of PPP/PPP-RTK is a sensibly increased accuracy (in GNSS-available areas), better than
10cm horizontal and 20cm vertical, however the same limitations (availability of positioning) of any
GNSS-based positioning technique are still present in challenging environments with limited GNSS
satellites visibility.
3. Simulations
In the frame of EMPHASIS project, the company-own simulation tool (PIPE) was upgraded to be
able to simulate 4G signal generation and signal reception, and to perform PVT in GNSS+INS+4G
integrated mode. In this way, it could be employed to assess the integrated GNSS+4G systems
performance (and GNSS+INS+4G) in a reference environment. The PIPE software has a modular
structure, in which different modules can work independently and provide output which would serve
as input to the next module. PIPE is able to generate realistic trajectories, generate GNSS
observations, generate GNSS, IMU and other sensors observations, and simulate antenna and receiver
– acquisition, tracking and PVT.
A simulation illustrating the positioning performance of GNSS+INS+4G has been set up and run.
The simulation consisted in three different scenarios, characterized by same simulated trajectory, at
the same time of the day, but different sky visibility conditions and different positioning systems
used:
1. Reference scenario of GNSS+INS navigation in a favorable environment with no GNSS
signals blockage
2. Scenario of GNSS+INS navigation with obstructed sky visibility (only two satellites visible)
3. Scenario of GNSS+INS+4G navigation again with obstructed sky visibility (only two
satellites visible), but three BSs always in LoS.

In the simulation, a vehicle is travelling at low speed (<50km/h) over a circuit of about 3km length
in sub-urban area. It is a 6 minutes’ drive around the block next to ADS headquarters in Ottobrunn.
Figure 4 shows the location for the simulated scenario, with the simulated position of the BSs, and the
reference 4G BS network considered. Navigation results for the run are given in Table 1 – positioning
accuracy was better than 5m in all directions (NEU).

Table 1 – Positioning performance in the simulated scenario
KPI Galileo (8 SVs) + INS Galileo (2 SVs) + INS Gal. (2 SVs) + INS + 4G
(3 BS)
STD North [m] 0.11 1574 0.88
STD East [m] 0.13 1790 1.07
STD Up [m] 0.22 515 1.14
Bias North [m] 0.38 1418 0.38
Bias East [m] -0.36 -1605 4.50
Bias Up [m] -0.08 494 -1.47
RMSE North [m] 0.40 2119 0.96
RMSE East [m] 0.38 2405 4.62
RMSE Up [m] 0.24 714 1.86

~75
0m

Figure 4 - Location for the simulation scenario (top) and reference 4G BS network (bottom, from
[6]).
Figure 5 - Horizontal positioning results for outlier and spoofing simulation scenarios. Top left:
nominal case (no anomalies/attacks injected); top right, outliers and spoofing attack injected,
no integrity monitoring algorithm implemented; bottom left, outliers and spoofing attack
injected, eRAIM algorithm implemented; bottom right, outliers and spoofing attack injected,
filterbank algorithm implemented.

Figure 6 - Flight-demo trajectory (left), network signal RSRP recorded at different altitudes
(middle-bottom) and positioning error results from the simulation run (right).

Additional simulations illustrating the positioning performance of GNSS+INS+4G in different
integrity-challenging scenarios have been set up and run. The scenarios analysed simulated the
occurrence of anomalies (outliers) and an external attack (spoofing). Figure 5 shows the positioning
results for the following scenarios:
1. Reference scenario (top left of Figure 5): the reference scenario consisted in GNSS+INS+4G
navigation in a partially sky-obstructed environment with visibility of 4-5 satellites, and 3 cellular
network BSs.
2. Challenging scenario (other three sub-plots of Figure 5): in the challenging (faulty) scenario,
single outliers are injected first, and later a spoofing attack is simulated, with a slowly growing error
simultaneously in the observations from 3 satellites. The outliers are jump errors, the first of 50m size
and the second of 20m. For the spoofing simulation, ramp errors starting with 5m size and reaching
over hundred meters size are injected.

In the top two sub-plots of Figure 5, no integrity monitoring algorithm was implemented, whereas,
in the bottom two, eRAIM was implemented on the left, and filterbank algorithm on the right. It can
be seen that the eRAIM algorithm is able to detect and exclude the outliers (single satellite faults), but
it is not able to cope with the anomaly affecting three channels at the same time. However, is able to
exclude one of the three spoofed satellites. The filterbank algorithm is instead able to cope with both
outliers’ faults and spoofing attack. The ramp errors are detected almost instantaneously.

After input from the flight-demo results obtained by the project partner Evektor, an additional
simulation was run in a new scenario reproducing the actual flight. Figure 6 shows the trajectory
flown by the Evektor aircraft during the flight-demo, the network signal RSRP registered as function
of the altitude, and the results of the simulated hybrid GNSS-LTE-INS navigation based on the
information on GNSS and LTE signals reception recorded during the flight. The positioning accuracy
recorded is better than one meter during the whole run; in fact, as the flight was performed in very sky
visibility conditions, the positioning performance is highly dominated by the GNSS performance (the
aiding from LTE is almost negligible).

4. Conclusions
PVT availability obtainable with GNSS only is not sufficient for critical applications, e.g. SoL
services run through GA/R operations, when flying below 500ft or in terminal areas with obstructed
sky visibility. With three GNSSs available, in urban areas the maximum PVT availability reachable is
estimated by ADS at about 94%. As a consequence, additional sensors, such as IMU for INS and/or
other signals of opportunities (e.g. RF network-based schemes), are required to offer a reliable
navigation service. Simulations have shown that INS/GNSS fusion can guarantee significant
improvement in navigation performance with respect to GNSS only, with a contained cost. Consumer
grade INS can guarantee an improvement of performance of both GNSS network-based standard
positioning technique (SPS) and precise positioning techniques (e.g. PPP), in environments with
degraded satellite visibility (e.g. urban and sub-urban). INS/GNSS fusion results particularly helpful
in enhancing the integrity of the navigation solution, as the INS provides redundancy of
measurements in all navigation scenarios, and it cannot be spoofed, complementing GNSS in most
aspects (especially in bridging outages). After design and implementation of network signals (4G)
processing methods, both Cramer-Rao bounds and PVT simulations have shown that 4G PRS signals,
when considering an average-to-high bandwidth, deliver a range positioning accuracy comparable to
GNSS or only slightly worse (range standard deviation of about 5m), in areas with densely distributed
4G network. Positioning accuracy for GNSS+INS+4G in a scenario with 2 satellites visible and 3 4G
Base Stations considered was better than 5m in all directions (NEU), under the assumption of good
visibility of network BSs and low multipath for network signals. Two Integrity Monitoring (IM)
algorithms, an eRAIM and a filterbank approach, based on adaptive filtering, were also reviewed and
implemented in the proposed navigation algorithm. Navigation simulations were run in different
scenarios, in nominal and faulty conditions, to test the robustness of the navigation solution. Outlier
faults and a spoofing attack were simulated. The outlier fault simulations showed that both eRAIM
and filterbank algorithms were able to detect and exclude jump errors in the observations, while the
spoofing attack simulation showed that the filterbank IM algorithm (based on adaptive filtering) is
robust also against threats affecting multiple channels at the same time, and it is able to detect and
exclude this type of anomaly within few seconds of its injection.
5. References

[1] W. Wang, J. Talvitie, E. J. Adamova, T. Fath, L. Korenciak, M. Valkama and E. S. Lohan.
”Empowering Heterogeneous Communication Data Links in General Aviation through mmWave
Signals.” accepted by IEEE Wireless Communications Magazine.
[2] Pitch on 5G at TechBites, 2018, http://techbites.fi/event/5g-and-beyond/
[3] https://aerospace.honeywell.com/en/pages/emphasis-project
[4] Míguez, J., Gisbert, J.V.P, Garcia-Molina, J.A., Zoccarato, P., Crosta, P., Ries, L., Pérez, R.O.,
Seco-Granados, G., Crisci, M., "Multi-GNSS Dynamic High Precision Positioning in Urban
Environment," Proceedings of the 30th International Technical Meeting of the Satellite Division
of The Institute of Navigation (ION GNSS+ 2017), Portland, Oregon, September 2017, pp. 408-
416.
[5] Teunissen, P. J. G., and Khodabandeh, A., "Review and principles of PPP-RTK methods."
Journal of Geodesy 89.3 (2015): 217-240.
[6] Knutti, F., Sabathy, M., Driusso, M., Mathis, H. and Marshall, C., Positioning using LTE signals,
Proceedings of Navigation Conference in Europe (pp. 1-8), April 2015.
[7] del Peral-Rosado, J.A., López-Salcedo, J.A., Zanier, F. and Seco-Granados, G., Position
accuracy of joint time-delay and channel estimators in LTE networks. IEEE Access, 6, pp.25185-
25199, 2018.
[8] del Peral-Rosado, J.A., López-Salcedo, J.A., Seco-Granados, G., Zanier, F. and Crisci, M.,
Achievable localization accuracy of the positioning reference signal of 3GPP LTE. In 2012
International Conference on Localization and GNSS (pp. 1-6). IEEE, 2012.
[9] del Peral-Rosado, J. A., R. Raulefs, J. A. López-Salcedo, and G. Seco Granados, Survey of
cellular mobile radio localization methods: From 1G to 5G, IEEE Commun. Surveys Tuts., vol.
20, no. 2, p. 25, 2nd Quart., 2018.
[10] del Peral-Rosado, J. A., J. A. López-Salcedo, G. Seco-Granados, F. Zanier, and M. Crisci, Joint
maximum likelihood time-delay estimation for LTE positioning in multipath channels,
EURASIP J. Adv. Signal Process., vol. 2014, no. 1, pp. 1-13, Mar. 2014.
[11] I. Güvenç and C.-C. Chong, A survey on TOA based wireless localization and NLOS mitigation
techniques, IEEE Commun. Surveys Tuts., vol. 11, no. 3, pp. 107124, 3rd Quart., 2009.
[12] Groves, P., Principles of GNSS, Inertial, and Multisensor Integrated Navigation Systems, Artech
House Publishers, Second Edition, 2013.
[13] B. W. Parkinson and P. Axelrad., Autonomous GPS integrity monitoring using the pseudorange
residual. NAVIGATION: Journal of the Institute of Navigation, edition 35(2), 1988.
[14] Wendel, J., Meister, O., Mönikes, R., GPS/INS Integrity Monitoring Using a Modified GPB1
Filter Bank, Proceedings of the 21st International Technical Meeting of the Satellite Division of
The Institute of Navigation (ION GNSS 2008), Savannah, GA, September 2008, pp. 1589-1595,
2008.
[15] 3GPP TS 36.305, Stage 2 functional specification of User Equipment (UE) positioning in E-
UTRAN (Rel. 9), Std.