An adapted RAIM algorithm for urban canyon environment

This paper evaluates the potential capacity of Receiver Autonomous Integrity Monitoring (RAIM) algorithms for Global Positioning System (GPS) and GPS Aided GEO Augmented Navigation (GAGAN) to support approach and landing phases of flight with vertical guidance. As the traditional RAIM does not support vertical guidance, Advanced RAIM (ARAIM) with potential to achieve worldwide coverage of vertical guidance, is used. These algorithms have focused on the Horizontal Protection Level (HPL) and Vertical Protection Level (VPL). User position is computed by detecting and excluding faults within the navigation solution and position accuracies are also provided. It is found that using RAIM, Position Dilution of Precision (PDOP) mean was good (1.5674) and Position Error (PE) was estimated to be 9.4042m with Fault Detection and Exclusion (FDE) implementation. While on the other hand, to increase horizontal and vertical accuracies, Advanced RAIM algorithm is implemented using GPS and GAGAN data. In case of GPS, Horizontal Protection Error (HPE) mean is 32.8541m and Vertical Protection Error (VPE) mean is 19.9901m. In case of GAGAN, HPE mean is 2.7190m and VPE mean is 3.3010m, thus achieving 95 percent accuracy requirement.

The field of GNSS integrity comprises a plethora of integrity related algorithms, each featured with different characteristics. These algorithms use a priori information of some parameters in order to provide integrity information to the user. One type of these algorithms, RAIM, is extensively used in the maritime domain in order to provide an indication if the position calculated is likely to be outside of the requirements of maritime performance standards, as it is required by IMO regulation. The term “Classical RAIM” refers to fully autonomous algorithms which can implement only one, a combination or all the following capabilities: Fault Detection, Fault Exclusion and Protection Level computation. In order to provide this indication, a GNSS receiver shall incorporate RAIM using at least Fault Detection (FD) algorithms, or similar means to determine if accuracy is within the performance standards and provide an integrity indication. In order to harmonise and ensure the correct RAIM algorithms implementation, its usage is standardised by the standard IEC 61108, in particular 1 and 3 series for GPS and Galileo constellations. The current RAIM definition in standards does not constrain the specific RAIM algorithm implementation deliberately in order to let the manufactures implement the most suitable one for their applications. In addition, in order to prove that a receiver is compliant with the requirements specified in this standard, two simple tests are proposed. The first one intends to test the performance of the receiver under safe and caution states, and the other one tests the unsafe state. However, as it is recognised by IALA in the last workshop on the future of marine radiobeacons, “current implementations of Receiver Autonomous Integrity Monitoring (RAIM) are considered inadequate due to the current lack of maritime specific RAIM algorithms.” It has been observed some limitation of current RAIM implementations beyond a specific algorithm for maritime. First of all, the relaxed requirements, in terms of high probabilities of false alarms and of not detecting an error condition, might be justified due to the limitations expected from some implementations of RAIM algorithms. In addition, requirements for GPS and Galileo RAIM differs significantly. Secondly, they are based on some hypothesis as single-failure assumption, a priory estimation of error values components (too conservative in order to provide the integrity required for any user under any condition) or the no existence of biases in faultfree measurements that may not ensure the integrity required if these hypothesis are not met in maritime domain. Finally, considering the simplicity of the aforementioned tests, which do not provides a set of parameters for testing or even assess the probabilities of miss-detection or false alarm, there is no assurance that the RAIM algorithm implemented in the receiver correctly provides the integrity required. To ensure this, it would be necessary to improve the test method in order to characterize the value of the introduced error and add new tests to evaluate the complete set of requirements to the implemented integrity algorithm. The GSA (European GNSS Agency), under GSALOT3TRANS framework contract, analysed the implementation of EGNSS in the area of transport applications. In particular, the Specific Contract 7 (SC7) MarTech it is being assessed the potential use of SBAS combined with RAIM in maritime and inland waterways (IWW) domains. The industrial partners of this specific contract are VVA Brussels (prime) and GMV. Although is not contemplated in any of the aforementioned regulations, the use of SBAS on top of other GNSS technologies that use RAIM may imply some important advantages. The first advantage and the most obvious of the SBAS corrections usage on top of RAIM is the increased performances in terms of accuracy, availability and continuity. The use of SBAS integrity information may also overcome the limitation of some RAIM algorithms that are only able to detect one faulty satellite. SBAS integrity messages also contains valuable information about the estimation of error components that may be used by the RAIM algorithm on real time with enough level of integrity to improve the performance. The aim of this paper is to provide a summary of the activities developed so far as part of GSALOT3TRANS SC7 regarding the current RAIM limitations in the maritime domain and the potential use of SBAS in combination with it to overcome some of these limitations.

This paper presents field test results of mobile positioning with signals of opportunity (SOOP) in urban and urban canyon environments and the lessons learned. The particular SOOP considered in this paper is the digital television (DTV) signals available in the United States, namely, ATSC-8VSB. The field tests include runs in downtown San Mateo and San Francisco Financial District, representing typical urban and urban canyon environments. DTV signals from six DTV stations together with IMU and GPS data are recorded aboard a ground vehicle. The field tests show that DTV signals are abundant in urban and urban canyon environments, contrary to a popular concern about signal availability due to blockage by high-risers. Positioning geometry is also not a problem even though the number of transmitters may be limited because the ranges to signal sources are relatively short and the resulting geometric dilution of precision (GDOP) is acceptable especially for the two-dimensional solutions. However, multipath is omnipresent, having two detrimental effects on ranging and positioning. Severe mobile fading is frequent that disrupts continuous tracking and non-line of sight (NLOS) signals introduce large errors to correlation peak based timing. To process multipath-dominant signals, a signal parameter estimation methodology is developed. In this approach, periodic signal patterns (field sync segments at 41 Hz) are searched for via correlation using a constant false alarm rate (CFAR) detector and their times of arrival (TOA) are extracted using the orthogonal matched pursuit (OMP) algorithm amidst multipath to form pseudorange measurements. Both standalone SOOP solutions and integrated SOOP/IMU solutions are generated for the test trajectories, which are then compared to GPS for performance evaluation. The study indicates that the processing algorithms presented in the paper can successfully detect the first arrival of SOOP in urban and urban canyon environments and extract its TOA precisely when the signals are available (out of fading or blockage). However, the timing information carried by such first arrivals, good enough to serve the primary purpose of communications, may not be so for ranging because of NLOS. As such, timing of first arrivals is not sufficient by itself for positioning and has to be used in conjunction with other data such as IMU, which is used in this paper. Yet, distinct and stable multipath signatures may be exploited, together with an environment map for instance, for persistent positioning in urban and urban canyon environments, which is a direction of our future research.

Combined multi-global navigation satellite system (GNSS) signals are capable of improving satellite availability for both standalone and differential positioning. Currently, the potential for highaccuracy automobile navigation using GNSS is constrained by severe multipath and poor satellite geometry, especially in “urban canyons” in large cities. With differential GNSS (D-GNSS) positioning, inconvenient system time differences can be removed by reference-station processing, allowing a user’s receiver position to be accurately calculated using four or more visible satellite signals. Therefore, in the future, we can filter numerous multi-GNSS measurements based on their quality in order to enhance the positioning performance in urban environments. In this paper, we present several methods that use multi-GNSS to filter signals from satellites containing severe multipath errors. In addition, we select single-frequency code-based D-GNSS because it has significant potential due to its low cost and robustness. The first method uses the measured carrier-to-noise ratio (C/N0). When only reflected signals are received in dense urban areas, the C/N0 will decrease by more than 6 dB-Hz, with the exception of high-elevation satellites. Thus, by comparing the measured and expected C/N0 at various elevation angles, we may be able to detect the presence of severe multipath signals. The second method involves using the error residual from the Receiver Autonomous Integrity Monitoring (RAIM), which is a well-known technique for checking the quality of measurements. Signals having severe multipath effects result in significant deterioration of measurements. In addition to the above methods, we introduce several points that should be noted in order to improve D-GNSS. To evaluate our proposed method, we perform positioning tests using a car in an urban environment. Differential positioning was used for multi-GNSS with GPS, QZSS, BeiDou, and GLONASS. We present an evaluation of each technique that is used to mitigate multipath errors. The results show that our proposed techniques effectively improved the horizontal accuracy. In addition, the accuracy of the horizontal errors was improved by more than 50% in two different environments.

Two Receiver Autonomous Integrity Monitoring (RAIM) architectures, Advanced RAIM (A-RAIM) and Relative RAIM (R-RAIM), are compared with two different RAIM algorithms, the Classic method and the Multiple Hypothesis Solution Separation (MHSS) method. The difference between A-RAIM and R-RAIM is in the positioning methods that produce different error models and projection matrices for integrity monitoring. The difference between RAIM algorithms lies in the methods of risk distribution. The influences of different positioning methods on integrity results are analysed in this paper via a generalized RAIM framework. Simulation results for the LPV-200 service with worldwide coverage show that the R-RAIM position domain method has the best results, while the differences between these methods decrease with application of the optimization method.

Urban areas are challenging environments for satellite navigation because of large multipath errors and frequent satellite signal loss. Urban air mobility (UAM) has a concept for operating aircraft in urban environments, where it is important to have accurate and integrity-assured positions. In response, this paper proposes a receiver autonomous integrity monitoring (RAIM) method using the time-differenced carrier phase (TDCP). TDCP measurements are robust to multipath and do not require the resolution of integer ambiguity because time differences eliminate any integer ambiguity. TDCP RAIM differentiates measurements at fixed time intervals and accumulates the estimated displacement vector. In this study, a general formulation for positioning and protection level of TDCP RAIM is introduced. The performance of TDCP RAIM was evaluated through simulation and validated using real urban measurement data, and was compared with that of Relative RAIM. The results indicate that TDCP RAIM is robust to changes in visible satellites and provides continuous positioning and protection level.

GNSS (“Global Navigation Satellite Systems”) applications with high security requirements usually manage integrity with Receiver Autonomous Integrity Monitoring (RAIM). Developed originally for aeronautics, RAIM techniques perform a consistency check on satellite measurements to provide a reliable positioning to the user. Modern versions of RAIM provide high performances for aviation. However, the problematics for terrestrial navigation, especially in urban environments, are quite different and have motivated the development of a new integrity process derived from the RAIM concept. In this paper, we introduce a new detection algorithm based on the a priori coherence between the direct received raw signals and the estimated position provided by the navigator. The use of raw satellite signals allows the detection of more estimation inconsistencies. The major differences between the proposed approach (a priori) and the RAIM approach (a posteriori) are outlined from a theoretical standpoint and illustrated by simulated data. Furthermore, we introduce a new criterion derived from both processes which proves their complementarity. Hence, this paper demonstrates the relevance of such a joint assessment in urban scenarios with degraded signal propagation conditions.

Currently, global navigation satellite system (GNSS) receivers can provide accurate and reliable positioning service in open-field areas. However, their performance in the downtown areas of cities is still affected by the multipath and none-line-of-sight (NLOS) receptions. This paper proposes a new positioning method using 3D building models and the receiver autonomous integrity monitoring (RAIM) satellite selection method to achieve satisfactory positioning performance in urban area. The 3D building model uses a ray-tracing technique to simulate the line-of-sight (LOS) and NLOS signal travel distance, which is well-known as pseudorange, between the satellite and receiver. The proposed RAIM fault detection and exclusion (FDE) is able to compare the similarity between the raw pseudorange measurement and the simulated pseudorange. The measurement of the satellite will be excluded if the simulated and raw pseudoranges are inconsistent. Because of the assumption of the single reflection in the ray-tracing technique, an inconsistent case indicates it is a double or multiple reflected NLOS signal. According to the experimental results, the RAIM satellite selection technique can reduce by about 8.4% and 36.2% the positioning solutions with large errors (solutions estimated on the wrong side of the road) for the 3D building model method in the middle and deep urban canyon environment, respectively.

Receiver autonomous integrity monitoring (RAIM) has long relied on GPS to achieve lateral navigation by different aerospace and aviation systems. However, an advanced form of RAIM, called ARAIM, would achieve the additional function of vertical navigation. However, because vertical operations require tighter integrity capabilities than what is currently achievable by RAIM, more stringent evaluations of GNSS performance has become a greater focus, especially as new satellite service constellations such as Galileo become more operationally mature. There are two categories of satellite faults that ARAIM requires knowledge of: satellite fault, which affects each satellite independently, and constellation fault, which affects multiple satellites simultaneously due to a common cause. By analyzing GNSS performance, estimates for the likelihood of each type of fault can be obtained and its impact on ARAIM performance can be assessed. Different fault likelihoods result in different safety comparisons, thus, it is important to evaluate the fault types and their probabilities of occurrence. This paper examines the last 3 years of Galileo clock and ephemeris errors to obtain appropriate estimates for the probability of independent satellite failures, Psat, and the probability of simultaneous satellite failures, Pconst. This paper also examines the two most recent GPS faults in 2022 and 2023 and near-faults from 2017 to 2021 given that there have been no GPS faults between 2012 and early 2022, but still some anomalous events worthy of analysis.

Satellite Navigation Receiver Autonomous Integrity Monitoring (RAIM) is developed for detection and recognition of satellite faults using the redundant observation values of receiver itself. This article first makes a comparative analysis to the conventional and recently proposed RAIM fault detection and identification methods, and then points out that the conventional fault identification methods have such weakness as low fault detection probability and high false alarm probability in the situation of simultaneous multiple faulty satellites, while the recently proposed multi-satellite fault identification methods require excessive computation work though enjoy a higher detection probability. To solve these problems, a new RAIM multiple satellite fault detection and recognition method is proposed in this paper, which is characterized by high detection probability, low false alarm probability and low computation load, practicable for project implementation. Based on a simulation analysis, it turns out that this method has a higher detection probability without false alarm at all. This method requires so low computation work that it only needs 2 m times of least squares residuals fault detection and m times of fault identification in m (m > 0) faulty satellites situation, showing a very promising application value.

Global Positioning System (GPS) satellites signal processing to obtain all in view satellite measurements and to use them to find a solution and to do integrity monitoring forms a major component of the load on the receiver's processing element. If processing capability is limited there is restriction on the number of measurements which can be obtained and processed. Alternatively, the number of measurements can be restricted and the resulting saving in load on the processor can be used to offer more spare processing time which can be used for other user specific requirements. Thus if m visible satellites can provide measurements only n measurements can be used (n < m). The arrangement and the number of GPS satellites influence measurement accuracy. Dilution of Precision (DOP) is an index evaluating the arrangement of satellites. Geometric DOP (GDOP) is, in effect, the amplification factor of pseudo-range measurement errors into user errors due to the effect of satellite geometry. The GDOP approximation is an essential feature in determining the performance of a positioning system. In this paper, knowledge-based methods such as neural networks and evolutionary adaptive filters are presented for optimum approximation of GDOP. Without matrix inversion required, the knowledge-based approaches are capable of evaluating all subsets of satellites and hence reduce the computational burden. This would enable the use of a high-integrity navigation solution without the delay required for many matrix inversions. Models validity is verified with test data. The results are highly effective techniques for GDOP approximation.

Integrity Monitoring (IM) for navigation systems is critical to ensure the safety of auto-driving vehicles. It refers to accurately raising alarms to a user when navigation positioning errors exceed the performance limitation. Although Receiver Autonomous Integrity Monitoring (RAIM) methods have been widely applied for Global Navigation Satellite System (GNSS) observations via a consistency checking algorithm, the integrity performance for auto-driving would suffer from a large degradation due to the low satellite visibility with signal occlusions and Non-Line-of-Sight (NLOS) receptions in urban environments. To alleviate this problem, the Fifth-generation (5G) communication signals are used as an auxiliary urban navigation source to increase the number of observations, and then an IM method for the integration of GNSS/5G (G5GIM) is proposed to improve the integrity performance. Specifically, the positioning reference signals of the 5G system in urban canyons are modeled to enrich the observations of the vehicle navigation, followed by the Horizontal Protection Level (HPL) estimation method and the fault detection algorithm for the integration of GNSS and 5G observations. Experimental results on the simulation and UrbanNav datasets show that the proposed G5GIM method significantly outperforms the existing GNSS RAIM method in terms of HPL reduction, fault detection rate and positioning accuracy improvement.

A global navigation satellite system (GNSS)-based navigation is a challenging task in a signal-degraded environments where GNSS signals are distorted by multipath and attenuated by fading effects: the navigation solution may be inaccurate or unavailable. A possible approach to improve accuracy and availability is the joint use of measurements from different GNSSs and quality check algorithms; this approach is investigated here using live GPS and Galileo signals. A modified receiver autonomous integrity monitoring (RAIM) algorithm, including geometry and separability checks, is proposed to detect and exclude erroneous measurements: the multi-constellation approach provides redundant measurements, and RAIM exploits them to exclude distorted observations. The synergy between combined GPS/Galileo navigation and RAIM is analyzed using live data; the performance is compared to the accuracy and availability of a GPS-only solution. The tests performed demonstrate that the methods developed are effective techniques for GNSS-based navigation in signal-degraded environments. The joint use of the multi-constellation approach and of modified RAIM algorithms improves the performance of the navigation system in terms of both accuracy and availability.

The positional accuracy of navigation receiver is an important factor for various applications. Based on the application, the achieved positional accuracy levels vary from meters to millimeters. IRNSS-GPS-SBAS (IGS) receiver is capable of receiving all the seven IRNSS satellite signals in L5 (1176.45MHz) and S1 (2492.028MHz) band in addition to twelve GPS satellite signals and two SBAS (GAGAN) satellite signals in L1 (1575.42 MHz) frequency band. In this paper the position accuracy is evaluated in terms of 2DRMS, 3DRMS CEP, SEP, Geometric Dilution of Precision (GDOP) and Doppler shift in various modes namely Hybrid (IRNSS L5 and GPS L1), IRNSS dual frequency (L5 and S1), IRNSS L5 only and IRNSS S1 only mode. In Hybrid mode, it is found that all the positional accuracy values are better than the corresponding other mode values.

In this paper, we focus on multipath channel characteristics of low-height antenna links for mobile to mobile communications in urban street canyon environments. We present a wideband MIMO channel sounder and antennas used to measure multipath channel characteristics in the 3.7GHz frequency band and the result of calibration test to evaluate a system performance before field measurement. We carried out channel measurement campaigns in typical urban street canyon environments in Seoul, Korea. The root mean square (r.m.s.) delay spread and angular spread characteristics are analyzed with results of their distribution and cumulative density function (CDF) in line of sight (LoS) and non-LoS (NLoS) case respectively.