NEW ALGORITHM FOR RECEIVER AUTONOMOUS INTEGRITY MONITORING

A new integrity metric for navigation systems is proposed based on the measurement domain. Proba-hilistic optimization design offers tools for fault detection by considering the required navigation performance （RNP） parameter and the uncertainty noise. The choice of the proper performance parameter provided the single-valued mapping with the missed detection probability estimates the probability of failure. The desirable characteristics of the residual sensitivity matrix are exploited to increase the efficiency for identifying erroneous observations. The algorithm can be used to support the performance specification and the efficient calculation of the integrity monitoring process. The simulation for non-precision approach （NPA） validates both the viability and the effectiveness of the proposed algorithm.

GNSS receiver autonomous integrity monitoring(RAIM)algorithm based on robust estimation

Integrity is significant for safety-of-life applications. Receiver autonomous integrity monitoring（RAIM） has been developed to provide integrity service for civil aviation. At first,the conventional RAIM algorithm is only suitable for single fault detection, single GNSS constellation. However, multiple satellite failure should be considered when more than one satellite navigation system are adopted. To detect and exclude multi-fault, most current algorithms perform an iteration procedure considering all possible fault model which lead to heavy computation burden. An alternative RAIM is presented in this paper based on multiple satellite constellations（for example, GPS and Bei Dou（BDS） etc.） and robust estimation for multi-fault detection and exclusion, which can not only detect multi-failures,but also control the influences of near failure observation. Besides, the RAIM algorithm based on robust estimation is more efficient than the current RAIM algorithm for multiple constellation and multiple faults. Finally, the algorithm is tested by GPS/Bei Dou data.

Multi‑level autonomous integrity monitoring method for multi‑source PNT resilient fusion navigation

For the integrity monitoring of a multi-source PNT(Positioning,Navigation,and Timing)resilient fusion navigation system,a theoretical framework of multi-level autonomous integrity monitoring is proposed.According to the mode of multi-source fusion navigation,the framework adopts the top-down logic structure and establishes the navigation source fault detection model based on the multi-combination separation residual method to detect and isolate the fault source at the system level and subsystem level.For isolated non-redundant navigation sources,the system level recovery verification model is used.For the isolated multi-redundant navigation sources,the sensor fault detection model optimized with the dimension-expanding matrix is used to detect and isolate the fault sensors,and the isolated fault sensors are verified in real-time.Finally,according to the fault detection and verification results at each level,the observed information in the fusion navigation solution is dynamically adjusted.On this basis,the integrity risk dynamic monitoring tree is established to calculate the Protection Level(PL)and evaluate the integrity of the multi-source integrated navigation system.The autonomous integrity monitoring method proposed in this paper is tested using a multi-source navigation system integrated with Inertial Navigation System(INS),Global Navigation Satellite System(GNSS),Long Baseline Location(LBL),and Ultra Short Baseline Location(USBL).The test results show that the proposed method can effectively isolate the fault source within 5 s,and can quickly detect multiple faulty sensors,ensuring that the positioning accuracy of the fusion navigation system is within 5 m,effectively improving the resilience and reliability of the multi-source fusion navigation system.

Receiver Autonomous Integrity Monitoring Availability and Fault Detection Capability Comparison Between BeiDou and GPS

This paper used the statistical methods of quality control to assess receiver autonomous integrity monitoring(RAIM) availability and fault detection(FD) capability of BeiDou14(Phase II with 14 satellites),BeiDou(Phase III with 35 satellites) and GPS(with 31 satellites) for the first time. The three constellations are simulated and their RAIM performances are quantified by the global, Asia-Pacific region and temporal variations respectively. RAIM availability must be determined before RAIM detection. It is proposed that RAIM availability performances from satellites and constellation geometry configuration are evaluated by the number of visible satellites(NVS, NVS > 5) and geometric dilution of precision(GDOP, GDOP < 6) together. The minimal detectable bias(MDB) and minimal detectable effect(MDE) are considered as a measure of the minimum FD capability of RAIM in the measurement level and navigation position level respectively. The analyses of simulation results testify that the average global RAIM performances for BeiDou are better than that for GPS except global RAIM holes proportion. Moreover, the Asia-Pacific RAIM performances for BeiDou are much better than that for GPS in all indexes. RAIM availability from constellation geometry configuration and RAIM minimum FD capability for BeiDou14 are better than that for GPS in Asia-Pacific region in all cases, but the BeiDou14 RAIM availability from satellites are worse than GPS's. The methods and conclusions can be used for RAIM prediction and real-time assessment of all kinds of Global Navigation Satellite Systems(GNSS) constellation.

Clock-based RAIM method and its application in GPS receiver positioning

Because the signals of global positioning system （GPS） satellites are susceptible to obstructions in urban environment with many high buildings around, the number of GPS useful satellites is usually less than six. In this case, the receiver autonomous integrity monitoring （RAIM） method earmot exclude faulty satellite. In order to improve the performance of RAIM method and obtain the reliable positioning results with five satellites, the series of receiver clock bias （RCB） is regarded as one useful satellite and used to aid RAIM method. From the point of nonlinear series, a grey-Markov model for predicting the RCB series based on grey theory and Markov chain is presented. And then the model is used for aiding RAIM method in order to exclude faulty satellite. Experimental results demonstrate that the prediction model is fit for predicting the RCB series, and with the clock-based RAIM method the faulty satellite can be correctly excluded and the positioning precision of GPS receiver can be improved for the case where there are only five useful satellites.

New methods for dual constellation single receiver positioning and integrity monitoring

Navigation system integrity monitoring is crucial for mission(e.g.safety)critical applications.Receiver autonomous integrity monitoring(RAIM)based on consistency checking of redundant measurements is widely used for many applications.However,there are many challenges to the use of RAIM associated with multiple constellations and applications with very stringent requirements.This paper discusses two positioning techniques and corresponding integrity monitoring methods.The first is the use of single frequency pseudorange-based dual constellations.It employs a new cross constellation single difference scheme to benefit from the similarities while addressing the differences between the constellations.The second technique uses dual frequency carrier phase measurements from GLONASS and the global positioning system for precise point positioning.The results show significant improvements both in positioning accuracy and integrity monitoring as a result of the use of two constellations.The dual constellation positioning and integrity monitoring algorithms have the potential to be extended to multiple constellations.

A GNSS Anti-Spoofing Technique Based on the Spatial Distribution Characteristic of the Residual Vectors

Anti-spoofing is becoming a crucial technique for applications with high navigation accuracy and reliability requirements.Anti-spoofing technique based on Receiver Autonomous Integrity Monitoring(RAIM)is a good choice for most Global Navigation Satellite System(GNSS)receivers because it does not require any change to the hardware of the receiver.However,the conventional RAIM method can only detect and mitigate a single spoofing signal.Some improved RAIM methods can deal with more spoofing signals,but the computational complexity increases dramatically when the number of satellites in view increase or need additional information.This paper proposes a new RAIM method,called the SRV-RAIM method,which has a very low computation complexity regardless of the number of satellites in view and can deal with any number of spoofing signals.The key to the new method is the spatial distribution characteristic of the Satellites'Residual Vectors(SRV).In replay or generative spoofing scenarios,the pseudorange measurements of spoofing signals are consistent,the residual vectors of real satellites and those of spoofing satellites have good separation characteristics in spatial distribution.Based on this characteristic,the SRV-RAIM method is proposed,and the simulation results show that the method can separate the real signals and the spoofing signals with an average probability of 86.55%in the case of 12 visible satellites,regardless of the number of spoofing signals.Compared to the conventional traversal-RAIM method,the performance is only reduced by 3.59%,but the computational cost is reduced by 98.3%,so most of the GNSS receivers can run the SRV-RAIM algorithm in time.

Correlation-weighted least squares residual algorithm for RAIM

The Least Squares Residual(LSR)algorithm,one of the classical Receiver Autonomous Integrity Monitoring(RAIM)algorithms for Global Navigation Satellite System(GNSS),presents a high Missed Detection Risk(MDR)for a large-slope faulty satellite and a high False Alarm Risk(FAR)for a small-slope faulty satellite.From the theoretical analysis of the high MDR and FAR cause,the optimal slope is determined,and thereby the optimal test statistic for fault detection is conceived,which can minimize the FAR with the MDR not exceeding its allowable value.To construct a test statistic approximate to the optimal one,the CorrelationWeighted LSR(CW-LSR)algorithm is proposed.The CW-LSR test statistic remains the sum of pseudorange residual squares,but the square for the most potentially faulty satellite,judged by correlation analysis between the pseudorange residual and observation error,is weighted with an optimal-slope-based factor.It does not obey the same distribution but has the same noncentral parameter with the optimal test statistic.The superior performance of the CW-LSR algorithm is verified via simulation,both reducing the FAR for a small-slope faulty satellite with the MDR not exceeding its allowable value and reducing the MDR for a large-slope faulty satellite at the expense of FAR addition.

An enhanced least squares residual RAIM algorithm based on optimal decentralized factor

The Least Squares Residual(LSR)algorithm is commonly used in the Receiver Autonomous Integrity Monitoring(RAIM).However,LSR algorithm presents high Missed Detection Risk(MDR)caused by a large-slope faulty satellite and high False Alert Risk(FAR)caused by a small-slope faulty satellite.In this paper,the LSR algorithm is improved to reduce the MDR for a large-slope faulty satellite and the FAR for a small-slope faulty satellite.Based on the analysis of the vertical critical slope,the optimal decentralized factor is defined and the optimal test statistic is conceived,which can minimize the FAR with the premise that the MDR does not exceed its allowable value of all three directions.To construct a new test statistic approximating to the optimal test statistic,the Optimal Decentralized Factor weighted LSR(ODF-LSR)algorithm is proposed.The new test statistic maintains the sum of pseudo-range residual squares,but the specific pseudo-range residual is weighted with a parameter related to the optimal decentralized factor.The new test statistic has the same decentralized parameter with the optimal test statistic when single faulty satellite exists,and the difference between the expectation of the new test statistic and the optimal test statistic is the minimum when no faulty satellite exists.The performance of the ODFLSR algorithm is demonstrated by simulation experiments.