Abstract:Abstract:The ionospheric bias and the combined observation noise are two crucial factors affecting the reliability of the triple-carrier ambiguity resolution (TCAR). In order to obtain a better reliability of TCAR, a new ionosphere-free and variance-restricted TCAR method is proposed through exploring the ambiguity link between each step of TCAR. The method constructs an ionosphere-free combination and simultaneously restricts the combined observation noise with respect to the wavelength to a sufficiently low … Show more
“…Therefore, extensive investigations have been conducted to improve the accuracy of the float ambiguities. These can be summarized as follows: (a) increasing the redundancy of measurements to enhance model strength, such as using multi-system or multifrequency signals [9], integrating other inertial measurement unit and Doppler velocity log sensors [10,11], and constructing dynamics, baseline, atmosphere, bias, or ambiguity-based constraints [12][13][14]; (b) designing multiply frequency combinations to reduce error interference, such as extra-wide lane or wide lane combinations, ionospheric reduced combinations, and ionosphere-free combinations [15,16]; (c) introducing optimal estimation methods by using historical information, such as sequential least-squares, Kalman filter, and factor graph [17]; and (d) modeling error precisely, such as multipath modeling, atmospheric modeling, and bias modeling [18][19][20]. These methods are beneficial for resolving ambiguities.…”
Ambiguity resolution is of critical importance to the carrier phase-based real-time kinematic (RTK) positioning method. Improving the accuracy of float ambiguities is beneficial for achieving ambiguity resolution. However, the large measurement noise from low-cost receivers will worsen the estimation accuracy of float ambiguities, which affects the ambiguity resolution performance. In this contribution, to reduce the influence of large measurement noise on ambiguity resolution for low-cost receivers, an improved RTK method for ambiguity resolution is proposed to enhance the accuracy of float ambiguities by equipping the rover receiver with common-antenna-based dual GNSS boards instead of only one GNSS board. First, the dual-board design can increase the measurement redundancy of the same frequency to suppress the measurement noise. Second, because the common-antenna design can form a moving zero-baseline between the dual GNSS boards, the ambiguities between them can be easily fixed. Known fixed ambiguities can be used as constraints to strengthen the positioning model. Simulation and real-world static and kinematic experiments were conducted to test the proposed method. The results demonstrate that the proposed method can improve the accuracy of float ambiguities by increasing the redundancy of the measurements and introducing the constraints of the ambiguities, and the improved accuracy is about 20 %. Compared with the traditional single-board RTK method, better ambiguity resolution performance can be achieved by taking advantage of the proposed common-antenna-based RTK method.
“…Therefore, extensive investigations have been conducted to improve the accuracy of the float ambiguities. These can be summarized as follows: (a) increasing the redundancy of measurements to enhance model strength, such as using multi-system or multifrequency signals [9], integrating other inertial measurement unit and Doppler velocity log sensors [10,11], and constructing dynamics, baseline, atmosphere, bias, or ambiguity-based constraints [12][13][14]; (b) designing multiply frequency combinations to reduce error interference, such as extra-wide lane or wide lane combinations, ionospheric reduced combinations, and ionosphere-free combinations [15,16]; (c) introducing optimal estimation methods by using historical information, such as sequential least-squares, Kalman filter, and factor graph [17]; and (d) modeling error precisely, such as multipath modeling, atmospheric modeling, and bias modeling [18][19][20]. These methods are beneficial for resolving ambiguities.…”
Ambiguity resolution is of critical importance to the carrier phase-based real-time kinematic (RTK) positioning method. Improving the accuracy of float ambiguities is beneficial for achieving ambiguity resolution. However, the large measurement noise from low-cost receivers will worsen the estimation accuracy of float ambiguities, which affects the ambiguity resolution performance. In this contribution, to reduce the influence of large measurement noise on ambiguity resolution for low-cost receivers, an improved RTK method for ambiguity resolution is proposed to enhance the accuracy of float ambiguities by equipping the rover receiver with common-antenna-based dual GNSS boards instead of only one GNSS board. First, the dual-board design can increase the measurement redundancy of the same frequency to suppress the measurement noise. Second, because the common-antenna design can form a moving zero-baseline between the dual GNSS boards, the ambiguities between them can be easily fixed. Known fixed ambiguities can be used as constraints to strengthen the positioning model. Simulation and real-world static and kinematic experiments were conducted to test the proposed method. The results demonstrate that the proposed method can improve the accuracy of float ambiguities by increasing the redundancy of the measurements and introducing the constraints of the ambiguities, and the improved accuracy is about 20 %. Compared with the traditional single-board RTK method, better ambiguity resolution performance can be achieved by taking advantage of the proposed common-antenna-based RTK method.
“…Compared with traditional GNSS systems with dual-frequency signals, triple-frequency measurements can significantly benefit precise satellite-based data processing, such as cycle slip detection [1][2][3], integer ambiguity resolution (AR) [4] for both baseline solutions [5][6][7][8], and precise point positioning (PPP) [9,10]. To alleviate the computational burden, we can select more special linear combinations.…”
Considering the influence of the ionosphere, troposphere, and other systematic errors on double-differenced ambiguity resolution (AR), we present an optimal triple-frequency code-phase combination determination method driven by both the model and the real data. The new method makes full use of triple-frequency code measurements (especially the low-noise of the code on the B3 signal) to minimize the total noise level and achieve the largest AR success rate (model-driven) under different ionosphere residual situations (data-driven), thus speeding up the AR by directly rounding. With the triple-frequency Beidou Navigation Satellite System (BDS) data collected at five stations from a continuously-operating reference station network in Guangdong Province of China, different testing scenarios are defined (a medium baseline, whose distance is between 20 km and 50 km; a medium-long baseline, whose distance is between 50 km and 100 km; and a long baseline, whose distance is larger than 100 km). The efficiency of the optimal code-phase combination on the AR success rate was compared with that of the geometry-free and ionosphere-free (GIF) combination and the Hatch-Melbourne-Wübbena (HMW) combination. Results show that the optimal combinations can always achieve better results than the HMW combination with B2 and B3 signals, especially when the satellite elevation angle is larger than 45 • . For the wide-lane AR which aims to obtain decimeter-level kinematic positioning service, the standard deviation (STD) of ambiguity residuals for the suboptimal combination are only about 0.2 cycles, and the AR success rate by directly rounding can be up to 99%. Compared with the HMW combinations using B1 and B2 signals and using B1 and B3 signals, the suboptimal combination achieves the best results in all baselines, with an overall improvement of about 40% and 20%, respectively. Additionally, the STD difference between the optimal and the GIF code-phase combinations decreases as the baseline length increases. This indicates that the GIF combination is more suitable for long baselines. The proposed optimal code-phase combination determination method can be applied to other multi-frequency global navigation satellite systems, such as new-generation BDS, Galileo, and modernized GPS.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.