MLAMBDA: a modified LAMBDA method for integer least-squares estimation

The least-squares ambiguity Decorrelation (LAMBDA) method has been widely used in GNSS for fixing integer ambiguities. It can also solve any integer least squares (ILS) problem arising from other applications. For real time applications with high dimensions, the computational speed is crucial. A modified LAMBDA (MLAMBDA) method is presented. Several strategies are proposed to reduce the computational complexity of the LAMBDA method. Numerical simulations show that MLAMBDA is (much) faster than LAMBDA. The relations between the LAMBDA method and some relevant methods in the information theory literature are pointed out when we introduce its main procedures.     

Orthogonality defect and reduced search-space size for solving integer least-squares problems

In the context of ambiguity resolution (AR) of global navigation satellite systems (GNSS), decorrelation among entries of an ambiguity vector, integer ambiguity search, and ambiguity validations are three standard procedures for solving integer least-squares problems. This paper contributes to AR issues from three aspects. Firstly, the orthogonality defect is introduced as a new measure of the performance of ambiguity decorrelation methods and compared with the decorrelation number and with the condition number, which are currently used as the judging criterion to measure the correlation of ambiguity variance–covariance matrix. Numerically, the orthogonality defect demonstrates slightly better performance as a measure of the correlation between decorrelation impact and computational efficiency than the condition number measure. Secondly, the paper examines the relationship of the decorrelation number, the condition number, the orthogonality defect, and the size of the ambiguity search space with the ambiguity search candidates and search nodes. The size of the ambiguity search space can be properly estimated if the ambiguity matrix is decorrelated well, which is shown to be a significant parameter in the ambiguity search progress. Thirdly, a new ambiguity resolution scheme is proposed to improve ambiguity search efficiency through the control of the size of the ambiguity search space. The new AR scheme combines the LAMBDA search and validation procedures together, which results in a much smaller size of the search space and higher computational efficiency while retaining the same AR validation outcomes. In fact, the new scheme can deal with the case there are only one candidate, while the existing search methods require at least two candidates. If there are more than one candidate, the new scheme turns to the usual ratio-test procedure. Experimental results indicate that this combined method can indeed improve ambiguity search efficiency for both the single constellation and dual constellations, respectively, showing the potential for processing high-dimension integer parameters in multi-GNSS environment.     

Fast integer least-squares estimation for GNSS high-dimensional ambiguity resolution using lattice theory

GNSS ambiguity resolution is the key issue in the high-precision relative geodetic positioning and navigation applications. It is a problem of integer programming plus integer quality evaluation. Different integer search estimation methods have been proposed for the integer solution of ambiguity resolution. Slow rate of convergence is the main obstacle to the existing methods where tens of ambiguities are involved. Herein, integer search estimation for the GNSS ambiguity resolution based on the lattice theory is proposed. It is mathematically shown that the closest lattice point problem is the same as the integer least-squares (ILS) estimation problem and that the lattice reduction speeds up searching process. We have implemented three integer search strategies: Agrell, Eriksson, Vardy, Zeger (AEVZ), modification of Schnorr–Euchner enumeration (M-SE) and modification of Viterbo-Boutros enumeration (M-VB). The methods have been numerically implemented in several simulated examples under different scenarios and over 100 independent runs. The decorrelation process (or unimodular transformations) has been first used to transform the original ILS problem to a new one in all simulations. We have then applied different search algorithms to the transformed ILS problem. The numerical simulations have shown that AEVZ, M-SE, and M-VB are about 320, 120 and 50 times faster than LAMBDA, respectively, for a search space of dimension 40. This number could change to about 350, 160 and 60 for dimension 45. The AEVZ is shown to be faster than MLAMBDA by a factor of 5. Similar conclusions could be made using the application of the proposed algorithms to the real GPS data.     

降相关对模糊度解算中搜索效率的影响分析

首先理论分析了条件数、正交缺陷度、S(A)等降相关评价指标所表示的几何意义,然后采用LAMBDA算法、LLL规约算法和Seysen规约算法通过模拟和实际数据对模糊度的搜索效果和不同评价指标之间的关系进行了深入计算分析。进一步验证得出"降低模糊度方差分量间的相关性实现最大程度地压缩椭球可以提高搜索效率"的观点是片面的,并通过结果分析表明提高搜索效率的本质在于尽可能地促使基向量按照一定方向排序。     

下三角Cholesky分解的整数高斯变换算法

针对全球导航卫星系统(GNSS)载波相位测量中,基于整数最小二乘估计准则解算整周模糊度问题。目前以LAMBDA降相关算法和Lenstra-Lenstra-Lovász(LLL)为代表的规约算法应用最为广泛。由于不同算法采用的模糊度方差-协方差阵的分解方式不同,导致难以合理地进行不同算法性能的比较。该文通过分析LAMBDA算法的降相关特点,从理论上推出基于下三角Cholesky分解多维情形下的整数高斯变换的降相关条件及相应公式,并与分解方式不同的LAMBDA和LLL算法作了对比。实验结果表明,降相关采用的分解方式将会直接影响计算复杂度和解算性能,因此该文推导的整数高斯变换算法便于今后基于下三角Cholesky分解的降相关算法间的合理比较。     

基于整周模糊度概率特性的有效性检验

准确确定载波相位整周模糊度是快速高精度GPS定位的关键,已有的检验GPS整周模糊度有效性的方法几乎均是基于其为非随机常量建立的,因而都存在一定的缺陷。本文在研究整周模糊度概率特性的基础上,提出一种基于LABMBAD算法的整周模糊度概率分布函数的检验方法。实际演算表明该方法简单有效,统计概念明确。     

利用两种z变换算法的PS-DInSAR相位解缠与等价性证明

在介绍PS-DInSAR相位解缠函数模型的基础上,给出了应用LAMBDA方法求解模糊度和形变参数的过程,并将两种改进的z变换降相关算法——逆整乔列斯基和LLL应用于PS-DInSAR相位解缠。以z变换过程的迭代次数、z变换后的模糊度向量间的平均相关系数和协因数阵的谱条件数为准则,对两种算法进行仿真模拟和分析,结果表明逆整乔列斯基算法和LLL算法等价。最后从理论上对两种降相关算法的一致性进行了解释。     

Parallel Cholesky-based reduction for the weighted integer least squares problem

The LLL reduction of lattice vectors and its variants have been widely used to solve the weighted integer least squares (ILS) problem, or equivalently, the weighted closest point problem. Instead of reducing lattice vectors, we propose a parallel Cholesky-based reduction method for positive definite quadratic forms. The new reduction method directly works on the positive definite matrix associated with the weighted ILS problem and is shown to satisfy part of the inequalities required by Minkowski’s reduction of positive definite quadratic forms. The complexity of the algorithm can be fixed a priori by limiting the number of iterations. The simulations have clearly shown that the parallel Cholesky-based reduction method is significantly better than the LLL algorithm to reduce the condition number of the positive definite matrix, and as a result, can significantly reduce the searching space for the global optimal, weighted ILS or maximum likelihood estimate.     

一种整周模糊度快速求解的改进LAMBDA方法

本文提出了一种改进LAMBDA方法:在确定Z变换后的模糊度时,改变以往对所有历元的模糊度全部进行搜索的做法,而是通过设置合理的条件,将搜索与直接归整有效地结合起来,从而减少了模糊度的解算时间,提高了解的效率。文章最后利用实测GPS数据验证了改进效果。     

回代解算的LAMBDA方法及其搜索空间

基于回代解算的序贯条件最小二乘技术和上三角的Cholesky分解算法,提出求解载波相位模糊度的一种新算法--回代解算的LAMBDA方法.该方法同Teunissen提出的LAMBDA方法相比,有着不同的目标函数和不同的搜索空间.实例试算表明这两种方法有着不同的执行过程,但有着相同的模糊度整数解和相当的搜索效率.     

Zero-correlation transformation and threshold for efficient GNSS carrier phase ambiguity resolution

The key point of accurate and precise applications of Global Navigation Satellite Systems lies in knowing how to efficiently obtain correct integer ambiguity. One of the methods in solving the ambiguity resolution problem is applying the ambiguity searching technique coupled with an ambiguity decorrelation technique. Traditionally, an integer-valued limitation of the transformation matrix ensures that the integer characteristic of candidates exists after the inverse transformation, but this also makes the decorrelation imperfect. In this research, the float transformation matrix will be considered. To ensure both the integer characteristic and perfect decorrelation can be reached, the float transformation is used indirectly. To solve the ambiguity resolution problem, the problem is transformed by integer and float transformation matrices. The objective of integer transformation is reducing the number of candidates. The target of float transformation is validating these reduced candidates. A zero correlation domain or a near complete diagonalization covariance matrix can be obtained via the float transformation. A space in this domain will be used as the threshold; hence the zero correlation domain is called the threshold domain. The number of ambiguity candidates based on integer transformation can be reduced once again through the proposed method. The experiments in this paper prove that the method can make the ambiguity resolution become more efficient without any drop in the accuracy.     

FirCAR算法的OTF快速定位方法

根据GNSS不同频率间整周模糊度的约束关系,提出一种基于多频整周模糊度间关系约束的模糊度新算法(dual-frequency integer relationship constrained ambiguity resolution,FirCAR)。FirCAR可快速动态解算出高高度角卫星的整周模糊度,将已经固定的整周模糊度视为高精度的伪距观测值应用到下一步的浮点解重算中。结合模糊度搜索算法,如LAMBDA,在模糊度搜索方面的高效性,根据重算后的浮点解进一步解算其他未固定的模糊度解。模糊度固定成功后,即可实现OTF(on the fly)快速定位。实测数据表明,FirCAR算法在静态和动态观测条件下,模糊度初始化所用的平均观测历元数分别为1.04和1.10。与常规的模糊度搜索算法的对比试验表明,结合FirCAR算法模糊度固定所用的观测历元数分别减少了39%和18%。     

一种适合于单频接收机快速模糊数求解的新方法

提出了一种适合于单频接收机的快速模糊数求解方法。结果表明 ,在用单频接收机的相对定位中 ,该方法快速、稳定     

整周模糊度整数变换前后LAMBDA方法的执行结果比较

首先介绍了求取模糊度整数解的整数最小二乘方法的基本原理和LAMBDA方法，然后讨论了降相关的可容许整数变换对于LAMBDA方法求取双差模糊度整数解的影响。通过一个短基线的实例计算发现：对原始的双差模糊度进行降相关的可容许整数变换，不仅可提高模糊度整数解的准确性，而且还能提高模糊度的求取速度。     

长距离网络RTK实时厘米级定位算法

针对CORS系统建设成本高和选址困难的问题,该文提出GPS长距离网络RTK定位算法。该算法首先利用MW组合观测方程解算基准站双差宽巷整周模糊度,采用Saastamoinen模型和GMF映射函数模型相结合解算双差对流层干分量延迟残差,并将双差对流层湿分量延迟残差作为未知参数进行估计,同时结合无电离层组合观测值解算基准站双差载波整周模糊度;然后,采用综合误差内插法解算基准站和流动站的误差改正数;最后,采用最小二乘法逐历元进行法方程叠加解算流动站双差模糊度浮点解,并利用LAMBDA算法和通过TIKHONOV正则化改进的LAMBDA算法搜索固定流动站双差宽巷整周模糊度和双差载波整周模糊度。实验表明,该算法能够将基准站间距离提高到100~150km,使流动站用户可以获得厘米级定位结果。     

基于LAMBDA和DC算法的GPS单历元整周模糊度的快速确定

仅利用LAMBDA方法求解GPS单历元整周模糊度成功率不高,并且当接收卫星数较多时搜索空间较大。为此,采用TIKHONOV正则化方法削弱单历元模型法方程的病态性,并且基于协方差矩阵选择部分宽巷模糊度,先采用LAMBDA方法进行搜索,再利用高解算效率的DC算法解算剩余宽巷模糊度,最后通过两组不同线性组合的逆变换直接求取原始观测值L1和L2的整周模糊度。实验和计算表明,方法显著提高整周模糊度的搜索效率,并且提高模糊度搜索成功率。     

地基伪卫星单历元三频组合逐级模糊度解算方法

为解决地基定位系统因基站固定导致几何多样性差,难以使用LAMBDA求解整周模糊度的问题.利用自差分双向时间同步原理,将双向观测值构建出消除钟差的公式.消去了时间误差的特性,将其作为双差测量值的替代,与三频模糊度解算(TCAR)算法相结合求解整周模糊度.在伪卫星平台的实验结果表明,能够实现快速单历元整周模糊度解算.     

Modified ambiguity function approach for GPS carrier phase positioning

This paper presents a new strategy for GPS carrier phase data processing. The classic approach generally consists of three steps: a float solution, a search for integer ambiguities, and a fixed solution. The new approach is based on certain properties of ambiguity function method and ensures the condition of integer ambiguities without the necessity of the additional step of the integer search. The ambiguities are not computed explicitly, although the condition of “integerness” of the ambiguities is ensured in the results through the least squares adjustment with condition equations in the functional model. An appropriate function for the condition equations is proposed and presented. The presented methodology, modified ambiguity function approach, currently uses a cascade adjustment with successive linear combinations of L1 and L2 carrier phase observations to ensure a correct solution. This paper presents the new methodology and compares it to the three-stage classic approach which includes ambiguity search. A numerical example is provided for 25 km baseline surveyed with dual-frequency receivers. All tests were performed using an in-house developed GINPOS software and it has been shown that the positioning results from both approaches are equivalent. It has also been proved that the new approach is robust to adverse effects of cycle slips. In our opinion, the proposed approach may be successfully used for carrier phase GPS data processing in geodetic applications.     

一种GPS整周模糊度单历元解算方法

仅利用单历元的载波相位观测值进行整周模糊度解算,观测方程秩亏,给单历元模糊度解算带来很大困难.因此,本文提出一种单历元确定GPS整周模糊度的方法.利用单历元测码伪距观测值和双频载波相位观测值组成双差观测方程,根据方差矩阵对宽巷模糊度进行分组,采用基于LABMDA方法的逐步解算方法来确定双差相位观测值的宽巷模糊度.确定宽...     

用遗传算法搜索GPS单频单历元整周模糊度

介绍了短基线利用单频单历元双差载波相位定位时模糊度固定的基本理论，探讨了利用遗传算法快速搜索GPS单频单历元整周模糊度的一些理论和实现的方法．提出了用改进的正则化方法改善浮动解来提高搜索成功率的新思路。算例分析表明，在一定的条件下．应用遗传算法搜索整周模糊度成功率高、稳键性较好。