GPS Receiver Autonomous Integrity Monitoring Research Articles

Fault detection and isolation in GPS receiver autonomous integrity monitoring based on chaos particle swarm optimization-particle filter algorithm

The receiver autonomous integrity monitoring (RAIM) is one of the most important parts in an avionic navigation system. Two problems need to be addressed to improve this system, namely, the degeneracy phenomenon and lack of samples for the standard particle filter (PF). However, the number of samples cannot adequately express the real distribution of the probability density function (i.e., sample impoverishment). This study presents a GPS receiver autonomous integrity monitoring (RAIM) method based on a chaos particle swarm optimization particle filter (CPSO-PF) algorithm with a log likelihood ratio. The chaos sequence generates a set of chaotic variables, which are mapped to the interval of optimization variables to improve particle quality. This chaos perturbation overcomes the potential for the search to become trapped in a local optimum in the particle swarm optimization (PSO) algorithm. Test statistics are configured based on a likelihood ratio, and satellite fault detection is then conducted by checking the consistency between the state estimate of the main PF and those of the auxiliary PFs. Based on GPS data, the experimental results demonstrate that the proposed algorithm can effectively detect and isolate satellite faults under conditions of non-Gaussian measurement noise. Moreover, the performance of the proposed novel method is better than that of RAIM based on the PF or PSO-PF algorithm.

Research on Particle Filter Based on Neural Network for Receiver Autonomous Integrity Monitoring

According to the measurement noise feature of GPS receiver and the degeneracy phenomenon of particle filter (PF), in order to alleviate the sample impoverishment problem for PF, GPS receiver autonomous integrity monitoring (RAIM) algorithm based on PF algorithm combining neural network was proposed, which was used to improve the importance state adjustment of particle filter algorithm. The PF algorithm based on neural network is analized. And the test statistic of satellite fault detection is set up. The satellite fault detection is undertaken by checking the cumulative log-likelihood ratio (LLR) of system state of GPS receiver.The proposed algorithm was Validated by the measured real raw data from GPS receiver, which are deliberately contaminated with the bias fault and ramp fault, the simulation results demonstrate that the proposed algorithm can accurately estimate the state of GPS receiver in the case of non-Gaussian measurement noise, effectively detect and isolate fault satellite by establishing log-likelihood ratio statistic for consistency test and improve the accuracy of detection performance.

Research on GPS Receiver Autonomous Integrity Monitoring Algorithm In the Occurrence of Two-satellite Faults

Reliability is an essential factor for GPS navigation system. Therefore, an integrity monitoring is considered as one of the most important parts for a navigation system. GPS receiver autonomous integrity monitoring (RAIM) technique can detect and isolate fault satellite. Based on particle filter, a novel RAIM method was proposed to detect two-satellite faults of the GPS signal by using hierarchical particle filter. It can deal with any system nonlinear and any noise distributions. Because GNSS measurement noise does not follow the Gaussian distribution perfectly, the particle filter can estimate the posterior distribution more accurately. In order to detect fault, the consistency test statistics is established through cumulative log-likelihood ratio (LLR) between the main and auxiliary particle filters (PFs).Specifically, an approach combining PF with the hierarchical filter is used in the process of two-satellite faults. Through GPS real measurement, the performance of the proposed GPS two-satellite faults detection algorithm was illustrated. Some simulation results are given to evaluate integrity monitoring performance of the algorithm. Validated by the real measurement data, the results show that the proposed algorithm can successfully detect and isolate the faulty satellite in the case of non-Gaussian measurement noise.

Research on GPS RAIM Algorithm Based on SIR Particle Filtering State Estimation and Smoothed Residual

The investigation presents a new approach based on SIR particle filtering state estimation and smoothed residual for GPS receiver autonomous integrity monitoring (RAIM), which adopted the difference value between the ideal observation values acquired by state estimation and the actual state observation values, and the log likelihood ratio (LLR) test based on probability density function of state-measurement was set up. Experimental results based on real GNSS data demonstrate that the algorithm can estimate the state precisely under non-Gaussian measurement noise, detect and isolate GPS satellite failures successfully and solve the performance degradation problem of RAIM algorithm based on Kalman filter. Therefore, experimental results validate the validity of SIR particle filtering state estimation and smoothed residual for RAIM.

Solution of the Two-Failure GPS RAIM Problem Under Worst-Case Bias Conditions: Parity Space Approach

With the advent of the GPS Wide Area Augmentation System (WAAS), there is increased interest in the receiver autonomous integrity monitoring (RAIM) multiple-failure problem. This paper shows how the horizontal and vertical protection level parameters (HPL and VPL) are affected by imposing a hypothetical worst-case two-failure requirement on the RAIM system. A numerical example is presented, and a short discussion of generalizing the method to more than two failures is also given. As might be expected, the paper indicates that the HPL and VPL parameters are increased significantly with the more demanding two-failure requirement as compared with detection of a single failure.

RAIM Availability for GPS Augmented with Barometric Altimeter Aiding and Clock Coasting1

In late 1991, the FAA formed a group called the Satellite Operational Implementation Team to accelerate the introduction of satellite navigation and communications into the National Airspace System (NAS). Since then, the team has been addressing major technical and operational issues that need to be resolved before GPS is used in instrument flight rules (IFR) operations in the NAS. One of the most critical criteria for the operational approval of near-term use of GPS in the NAS is availability of receiver autonomous integrity monitoring (RAIM) detection and identification functions. To improve RAIM availability, SOFT members suggested that relatively simple GPS augmentations in the form of barometric altimeter aiding and clock coasting be considered. This paper analyzes GPS RAIM availability with these augmentations and presents the technical analyses used by the team to support its recommendations.

RAIM Availability for Supplemental GPS Navigation

This paper examines GPS receiver autonomous integrity monitoring (RAIM) availability for supplemental navigation based on the approximate radial-error protection (ARP) method. This method applies ceiling levels for the ARP figure of merit to screen out bad detection geometries under worst-case bias conditions. The ARP criterion value for each phase of flight is based on the integrity specifications stated in the RTCA Special Committee (SC)-159 supplemental Minimum Operational Performance Standards (MOPS) for GPS. Applying the ARP criterion, extensive analysis was performed to determine the availability of RAIM over the conterminous United States, North Atlantic, Europe, Central East Pacific, and North Pacific during en route, terminal, and nonprecision approach phases of flight. The 21 primary, optimal 21, and optimized 21 + 3 GPS constellations were examined. The results demonstrate that RAIM is not available 100 percent of the time, even with 24 operational satellites. This is because there are times when only 4 satellites are visible, preventing RAIM detection altogether, and other times when the geometry of the visible satellites has an ARP that exceeds the ARP ceiling value.

A Baseline GPS RAIM Scheme and a Note on the Equivalence of Three RAIM Methods

The RTCA GPS Minimum Operational Performance Standards (MOPS) have now been released, and airborne equipment manufacturers will be expected to meet the specifications therein. A considerable portion of the MOPS is devoted to GPS integrity requirements and the associated receiver testing procedures. The GPS Integrity Channel (GIC) is still a few years away, so some form of Receiver Autonomous Integrity Monitoring (RAIM) must be relied upon in the interim period (and perhaps beyond). Many different RAIM schemes have been proposed over the past few years, each with its respective advantages and disadvantages. This paper proposes a baseline RAIM scheme that can serve as a standard for performance comparisons. The proposed scheme is based on a unified theory which says that under the condition of equal alarm rates, the range-comparison, least-squares-residuals, and parity RAIM methods all yield identical results. This scheme is a straightforward, workable RAIM method that is easily understood by all. It is a good scheme, but there is no claim that it is optimal.

Receiver autonomous integrity monitoring (RAIM) capability for sole-means GPS navigation in the oceanic phase of flight

Receiver autonomous integrity monitoring (RAIM), a GPS integrity monitoring scheme that uses redundant ranging signals to detect a satellite malfunction that results in a large range error, involves two functions: detection of the presence of a malfunctioning satellite and identification of which satellite (or satellites) is malfunctioning. An analysis is presented of GPS RAIM capability for sole-means navigation in the oceanic phase of flight, where the position protection limit requirement for the integrity function is not as stringent as for nonprecision approaches, and yet both detection and identification function may be required if GPS is to be used as a sole-means system. For this purpose, a detection and identification algorithm is developed which takes advantage of the fact that for the oceanic phase of flight, a much larger position error is acceptable than for the nonprecision approach phase of flight. The performance of this algorithm and an algorithm proposed previously by others is estimated via simulation and compared. On the basis of the results, recommendations are made on how RAIM may be used if GPS is to be coupled with an inertial system to provide a sole-means capability in the oceanic phase of flight.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

SATZAP: A Novel Approach to GPS Integrity*

Integrity continues to be a major issue preventing user acceptance of GPS. Substantial effort has therefore been invested in the pursuit of failure detection and warning system (FDWS) concepts to improve upon the existing integrity of the GPS positioning services. Notable progress has been made towards FDWS approaches, such as an independent GPS integrity channel (GIC) and receiver autonomous integrity monitoring (RAIM). This paper presents the conceptual outline of a new FDWS called “SATZAP.” It is a novel approach that takes maximum advantage of existing GPS resources. It utilizes the operational control system (OCS) and on-orbit Block II space vehicles (SVs) already built by the Department of Defense. Its user warning method is unique amongst FDWSs. Failed SVs would simply be turned “off” as far as the user is concerned. Turning an SV “off” within the integrity time limit is inherently compatible with all types of GPS receiver equipment; absolutely no user receiver modifications are required, and the warning cannot be misinterpreted.