The probability distribution of the ambiguity bootstrapped GNSS baseline

 The purpose of carrier phase ambiguity resolution is to improve upon the quality of the estimated global navigation satellite system baseline by means of the integer ambiguity constraints. However, in order to evaluate the quality of the ambiguity resolved baseline rigorously, its probability distribution is required. This baseline distribution depends on the random characteristics of the estimated integer ambiguities, which in turn depend on the chosen integer estimator. In this contribution is presented an exact and closed-form expression for the baseline distribution in the case that use is made of integer bootstrapping. Also presented are the bootstrapped probability mass function and easy-to-compute measures for the bootstrapped baseline's probability of concentration. Received: 28 September 2000 / Accepted: 11 January 2001     

Analysis of long-range network RTK during a severe ionospheric storm

The network-based GPS technique provides a broad spectrum of corrections to support RTK (real-time kinematic) surveying and geodetic applications. The most important among them are the ionospheric corrections generated in the reference network. The accuracy of these corrections depends upon the ionospheric conditions and may not always be sufficient to support ambiguity resolution (AR), and hence accurate GPS positioning. This paper presents the analyses of the network-derived ionospheric correction accuracy under extremely varying – quiet and stormy – geomagnetic and ionospheric conditions. In addition, the influence of the correction accuracy on the instantaneous (single-epoch) and on-the-fly (OTF) AR in long-range RTK GPS positioning is investigated, and the results, based on post-processed GPS data, are provided. The network used here to generate the ionospheric corrections consists of three permanent stations selected from the Ohio Continuously Operating Reference Stations (CORS) network. The average separation between the reference stations was ∼200 km and the test baseline was 121 km long. The results show that, during the severe ionospheric storm, the correction accuracy deteriorates to the point when the instantaneous AR is no longer possible, and the OTF AR requires much more time to fix the integers. The analyses presented here also outline the importance of the correct selection of the stochastic constraints in the rover solution applied to the network-derived ionospheric corrections.     

The least-squares ambiguity decorrelation adjustment: its performance on short GPS baselines and short observation spans

The least-squares ambiguity decorrelation adjustment is a method for fast GPS double-difference (DD) integer ambiguity estimation. The performance of the method will be discussed, and although it is stressed that the method is generally applicable, attention is restricted to short-baseline applications in the present contribution. With reference to the size and shape of the ambiguity search space, the volume of the search space will be introduced as a measure for the number of candidate grid points, and the signature of the spectrum of conditional variances will be used to identify the difficulty one has in computing the integer DD ambiguities. It is shown that the search for the integer least-squares ambiguities performs poorly when it takes place in the space of original DD ambiguities. This poor performance is explained by means of the discontinuity in the spectrum of conditional variances. It is shown that through a decorrelation of the ambiguities, transformed ambiguities are obtained which generally have a flat and lower spectrum, thereby enabling a fast and efficient search. It is also shown how the high precision and low correlation of the transformed ambiguities can be used to scale the search space so as to avoid an abundance of unnecessary candidate grid points. Numerical results are presented on the spectra of conditional variances and on the statistics of both the original and transformed ambiguities. Apart from presenting numerical results which can typically be achieved, the contribution also emphasizes and explains the impact on the method's performance of different measurement scenarios, such as satellite redundancy, single vs dual-frequency data, the inclusion of code data and the length of the observation time span. Received: 31 October 1995 / Accepted: 21 March 1997     

GPS姿态测量中模糊度的快速解算

针对GPS姿态测量对模糊度的解算要求准确快速的特点,首先,从减少运算量入手,通过减少运算量,提高解算速度;其次,并根据姿态测量基线长度已知这一特点,来提高模糊度固定的准确度。基于上述两点提出了一种新的模糊度快速解算方法。     

Influence of ambiguity precision on the success rate of GNSS integer ambiguity bootstrapping

In this contribution, we study the dependence of the bootstrapped success rate on the precision of the GNSS carrier phase ambiguities. Integer bootstrapping is, because of its ease of computation, a popular method for resolving the integer ambiguities. The method is however known to be suboptimal, because it only takes part of the information from the ambiguity variance matrix into account. This raises the question in what way the bootstrapped success rate is sensitive to changes in precision of the ambiguities. We consider two different cases. (1) The effect of improving the ambiguity precision, and (2) the effect of using an approximate ambiguity variance matrix. As a by-product, we also prove that integer bootstrapping is optimal within the restricted class of sequential integer estimators.     

Carrier phase-based integrity monitoring for high-accuracy positioning

Pseudorange-based integrity monitoring, for example receiver autonomous integrity monitoring (RAIM), has been investigated for many years and is used in various applications such as non-precision approach phase of flight. However, for high-accuracy applications, carrier phase-based RAIM (CRAIM), an extension of pseudorange-based RAIM (PRAIM) must be used. Existing CRAIM algorithms are a direct extension of PRAIM in which the carrier phase ambiguities are estimated together with the estimation of the position solution. The main issues with the existing algorithms are reliability and robustness, which are dominated by the correctness of the ambiguity resolution, ambiguity validation and error sources such as multipath, cycle slips and noise correlation. This paper proposes a new carrier phase-based integrity monitoring algorithm for high-accuracy positioning, using a Kalman filter. The ambiguities are estimated together with other states in the Kalman filter. The double differenced pseudorange, widelane and carrier phase observations are used as measurements in the Kalman filter. This configuration makes the positioning solution both robust and reliable. The integrity monitoring is based on a number of test statistics and error propagation for the determination of the protection levels. The measurement noise and covariance matrices in the Kalman filter are used to account for the correlation due to differencing of measurements and in the construction of the test statistics. The coefficient used to project the test statistic to the position domain is derived and the synthesis of correlated noise errors is used to determine the protection level. Results from four cases based on limited real data injected with simulated cycle slips show that residual cycle slips have a negative impact on positioning accuracy and that the integrity monitoring algorithm proposed can be effective in detecting and isolating such occurrences if their effects violate the integrity requirements. The CRAIM algorithm proposed is suitable for use within Kalman filter-based integrated navigation systems.

对Blewitt周跳探测与修复方法的改进

在简单介绍Blewitt方法的基础上，针对其存在的一些问题，在野值剔除、周跳探测与修复和模糊度解算方面提出了新思路和算法，从误差角度讨论该方案的可行性．实例分析表明：改进后的方法对周跳探测更“干净”、合理、可行．     

An approach to GLONASS ambiguity resolution

 When processing global navigation satellite system (GLONASS) carrier phases, the standard double-differencing (DD) procedure cannot cancel receiver clock terms in the DD phase measurement equations due to the multiple frequencies of the carrier phases. Consequently, a receiver clock parameter has to be set up in the measurement equations in addition to baseline components and DD ambiguities. The resulting normal matrix unfortunately becomes singular. Methods to deal with this problem have been proposed in the literature. However, these methods rely on the use of pseudo-ranges. As pseudo-ranges are contaminated by multi-path and hardware delays, biases in these pseudo-ranges are significant, which may result in unreliable ambiguity resolution. A new approach is addressed that is not sensitive to the biases in the pseudo-ranges. The proposed approach includes such steps as converting the carrier phases to their distances to cancel the receiver clock errors, and searching for the most likely single-differenced (SD) ambiguity. Based on the results from the theoretical investigation, a practical procedure for GLONASS ambiguity resolution is presented. The initial experimental results demonstrate that the proposed approach is useable in cases of GLONASS and combined global positioning system (GPS) and GLONASS positioning. Received: 19 August 1998 / Accepted: 12 November 1999     

基于不同模糊度分解方法的GPS导航卫星定轨研究

介绍了利用准电离层（QIF）方法和MW（Melbourne—Wubbena）方法进行模糊度固定的原理,在得到的卫星轨道浮点解的基础上,用两种方法分别进行了模糊度的固定。并分析了两种方法对于不同长度基线的模糊度固定成功率。结果显示：在固定模糊度的成功率上,Mw方法优于QIF方法,在基线长度为1000~4000km时,两种方法都保持着较高的模糊度固定成功率。     

A performance comparison of single and dual frequency GPS ambiguity resolution strategies

The impact of observation selection, observation combination and model parameterization on GPS carrier phase ambiguity resolution and position accuracy under operational conditions is investigated. The impact of an ionospheric bias for a generic linear combination of L1 and L2 measurements is assessed and the results are used to clearly outline the desirable characteristics for improving ambiguity resolution versus positioning accuracy performance. Ambiguity resolution performance and position accuracy are shown for widelane (WL), L1-only, and ionospheric-free (IF) combinations. Several techniques for dealing with the ionospheric bias are also presented and compared, including stochastic ionospheric modelling. Multiple carrier phase combination solutions estimated in the same filter are also compared. The concept of an optimal processing strategy—in terms of both reliable ambiguity resolution and high accuracy positions—is presented. In total, eight strategies, which vary in observables and parameters, are tested on several datasets ranging from 13 km to 43 km.