Signal Processing Techniques for the Integrity of Navigation for Land Users (INLU)

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While for the aviation related safety of life services GNSS integrity concepts have been developed and are used in Space Based Augmentation Systems like EGNOS and WAAS, integrity algorithms for non-aviation users have not yet been developed with the same level of maturity. However, new services for land users require integrity information as well. The major difference compared to the airborne user is the threat space the land user is face with: While in the aviation domain mainly system level errors need to be considered, additional sources of error for the land user are local threats like multipath, NLOS tracking, signal blockages and interference.

The INLU activity identifies possible land-user applications and preliminarily selects the most prospective candidates, for which integrity requirements are derived and tailored integrity algorithms are developed. These integrity algorithms are implemented in the INLU testbed. This testbed offers extensive scenario generation capabilities, including trajectory generation, constellation simulation, multipath generation according to the ITU-R-p.681 and other models, as well as NLOS and interference threat generation. The GNSS baseband samples representative for the scenario under test – which are either generated by the testbed itself or recorded using a Space Segment simulator steered by the testbed – are processed in a versatile software receiver, which allows combining various acquisition, tracking, multipath mitigation, consistency check and integrity algorithms. Besides stand-alone PVT solvers, several integration architectures with additional sensors, including tight and ultra-tight coupling with inertial navigation, and algorithms tailored to the train environment are available as well. The INLU testbed also covers means for analyzing the integrity performance of the algorithms under test, which allows first of all to identify the optimal combination of algorithms, second to quantify the achievable protection levels, integrity risks and availabilities for each specific application and threat scenario.

Users and their needs

INLU targets all user groups that have a need for GNSS PVT integrity in a land user environment. This includes the provision of protection levels for given integrity risks. The applications requiring integrity can be divided in two groups: The first group of applications require integrity, because the use of the GNSS PVT is safety critical. Examples for such applications are:

  • Train signalling, realization of the virtual balise concept
  • Advanced Driver Assistance Systems (ADAS)
  • Automatic guidance

The second group of applications require integrity, because the GNSS PVT results in consequences, which in some cases must be justifiable in court. Examples for such applications are: 

·         Road tolling using on-board units

·         Asset tracking, e.g. rental cars

·         Documentation of accidents

A global transportation company, which is active in the field of railway signalling and integrated transport systems for passenger traffic and freight operations, is partner of the INLU project, which contributes to the feasibility assessment and algorithm design activities of this company for satellite-based train control systems.  

Benefits

The INLU project defines the next generation PVT and integrity algorithms for satellite navigation users operating in urban and rural environments. 

Features

The INLU toolchain is composed of two major building blocks: The scenario generation modules and the processing modules, the latter forming the Positioning and Integrity Performance Evaluator (PIPE).

 The INLU scenario generation modules are illustrated in the figure below. Based on a user defined trajectory, constellation data, multipath and threat models, the scenario generator generates GNSS baseband samples. Alternatively, the scenario generator can be used to control a Radio Frequency Constellation Simulator (RFCS), which produces a RF signal like it would be available from a GNSS antenna. This signal can be provided to a front-end connected to a sampler, which stores GNSS baseband samples to disc. Furthermore, INLU offers capabilities to generate inertial sensor data, magnetometer data, baro-altimeter data and odometer data. The baseband samples, either generated by the INLU tools, recorded using a RFCS or recorded in test drives, are provided to the PIPE tools for further processing.  

The PIPE building blocks are illustrated in the figure below. A variety of tracking techniques can be used to obtain pseudorange, carrier phase and Doppler measurements. Different consistency checks can be applied to exclude faulty measurements, e.g. in case of NLOS tracking or when a tracker locked to a side peak of a BOC signal. These consistency checks assess e.g. distortions of the correlation function or check for discontinuities in the measurement histories. The measurements that pass these checks are processed in a PVT solver to obtain GNSS position and time. Hereby, a variety of PVT solvers are available, which can be combined with classical RAIM and ARAIM algorithms. Special ARAIM algorithms tailored to the train environment are available. For solvers which integrate the GNSS measurements with additional sensor data, integrity algorithms are available as well, mostly based on filter bank approaches. Finally, the INLU testbed offers various analysis tools to assess the integrity performance of the algorithms under test.

Current Status

The main building blocks of the INLU testbed are implemented and validated. An additional mode of operation, where instead of explicitly performing correlations with baseband samples the correlation results are calculated semi-analytically based on the tracking errors obtained from comparison with an ideal reference, is currently under development. For the most promising land user applications that have been selected in the first phase of the project, representative scenarios are in preparation, which will be processed in an extensive simulation campaign, revealing the achievable integrity performance with an optimal selection of algorithms. The project will be completed in 2016.  

Prime Contractor

Subcontractor

Project Managers

Contractor Project Manager

Dr. Jan Wendel
Airbus Defence and Space GmbH
81663 Munich
Germany
+49 89 607 33833

ESA Project Manager

Rigas Ioannides
ESTEC
Keplerlaan 1, P.O. Box 299
2200 Noordwijk
Netherlands

Status Date

24 October 2016 - Created: 28 January 2016