An Efficient Implementation of Fixed Failure-Rate Ratio Test for GNSS Ambiguity Resolution

Recently, the integration of an inertial navigation system (INS) and the Global Positioning System (GPS) with a two-antenna GPS receiver has been suggested to improve the stability and accuracy in harsh environments. As is well known, the statistics of state process noise and measurement noise are critical factors to avoid numerical problems and obtain stable and accurate estimates. In this paper, a modified extended Kalman filter (EKF) is proposed by properly adapting the statistics of state process and observation noises through the innovation-based adaptive estimation (IAE) method. The impact of innovation perturbation produced by measurement outliers is found to account for positive feedback and numerical issues. Measurement noise covariance is updated based on a remodification algorithm according to measurement reliability specifications. An experimental field test was performed to demonstrate the robustness of the proposed state estimation method against dynamic model errors and measurement outliers.

“…Otherwise, state uncertainties larger than

…”

Section: Adaptive Noise Covariancementioning

confidence: 99%

A Modified Extended Kalman Filter for a Two-Antenna GPS/INS Vehicular Navigation System

Hao

Xin

et al. 2018

“…The threshold function method is independent from ambiguity dimension and underlying function model and it was proposed for the difference test. Although this method is also attempted in the ratio test but it becomes more complex than the difference test case [ 33 ]. The method to mitigate computation burden for OIA has not been systematically studied.…”

Section: Generalized Difference Testmentioning

confidence: 99%

Improving GNSS Ambiguity Acceptance Test Performance with the Generalized Difference Test Approach

Wang

Chen

Shen

et al. 2018

In Global navigation satellite system (GNSS) data processing, integer ambiguity acceptance test is considered as a challenging problem. A number of ambiguity acceptance tests have been proposed from different perspective and then unified into the integer aperture estimation (IA) framework. Among all the IA estimators, the optimal integer aperture (OIA) achieves the highest success rate with the fixed failure rate tolerance. However, the OIA is of less practical appealing due to its high computation complexity. On the other hand, the popular discrimination tests employ only two integer candidates, which are the essential reason for their sub-optimality. In this study, a generalized difference test (GDT) is proposed to exploit the benefit of including three or more integer candidates to improve their performance from theoretical perspective. The simulation results indicate that the third best integer candidates contribute to more than 70% success rate improvement for integer bootstrapping success rate higher than 0.8 case. Therefore, the GDT with three integer candidates (GDT3) achieves a good trade-off between the performance and computation burden. The threshold function is also applied for rapid determination of the fixed failure rate (FF)-threshold for GDT3. The performance improvement of GDT3 is validated with real GNSS data set. The numerical results indicate that GDT3 achieves higher empirical success rate while the empirical failure rate remains comparable. In a 20 km baseline test, the success rate GDT3 increase 7% with almost the same empirical failure rate.

“…In the proposed approach, the Least-squares AMBiguity Decorrelation Adjustment (LAMBDA) method [29,30] was applied for ambiguity resolution to obtain the integer ambiguities (fixed solution) after obtaining the float estimates of the ambiguities. For validating the integer ambiguity estimates, there are two widely used methods, i.e., the traditional ratio test (RT) and the fixed failure-rate ratio test (FF-RT) [31,32,33,34,35,36]. The traditional RT approach adopts a fixed critical threshold which is usually chosen from experience, e.g., 1.5, 2, or 3 [26,37].…”

Section: System Design Scheme and Implementationmentioning

confidence: 99%

Smart Device-Supported BDS/GNSS Real-Time Kinematic Positioning for Sub-Meter-Level Accuracy in Urban Location-Based Services

Wang

Zhao

et al. 2016

Using mobile smart devices to provide urban location-based services (LBS) with sub-meter-level accuracy (around 0.5 m) is a major application field for future global navigation satellite system (GNSS) development. Real-time kinematic (RTK) positioning, which is a widely used GNSS-based positioning approach, can improve the accuracy from about 10–20 m (achieved by the standard positioning services) to about 3–5 cm based on the geodetic receivers. In using the smart devices to achieve positioning with sub-meter-level accuracy, a feasible solution of combining the low-cost GNSS module and the smart device is proposed in this work and a user-side GNSS RTK positioning software was developed from scratch based on the Android platform. Its real-time positioning performance was validated by BeiDou Navigation Satellite System/Global Positioning System (BDS/GPS) combined RTK positioning under the conditions of a static and kinematic (the velocity of the rover was 50–80 km/h) mode in a real urban environment with a SAMSUNG Galaxy A7 smartphone. The results show that the fixed-rates of ambiguity resolution (the proportion of epochs of ambiguities fixed) for BDS/GPS combined RTK in the static and kinematic tests were about 97% and 90%, respectively, and the average positioning accuracies (RMS) were better than 0.15 m (horizontal) and 0.25 m (vertical) for the static test, and 0.30 m (horizontal) and 0.45 m (vertical) for the kinematic test.