Characteristics of GPS positioning error with non-uniform pseudorange error

Fan, Jiangtao; Ma, Guanyi

doi:10.1007/s10291-013-0359-z

Cited by 10 publications

(7 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The constrained least squares method can obtain the IED for illuminated voxels without iteration and initial guess [15,32]. Moreover, the singular value decomposition (SVD) is a desirable choice since it gives a numerically stable solution in a compact and self-contained expression [73]. In voxel-based CIT, the combination of satellite and receiver produces numerous rays, while a part of observations is redundant.…”

Section: Singular Value Decompositionmentioning

confidence: 99%

A Review of Voxel-Based Computerized Ionospheric Tomography with GNSS Ground Receivers

Wan

2021

Remote Sensing

Self Cite

View full text Add to dashboard Cite

Ionized by solar radiation, the ionosphere causes a phase rotation or time delay to trans-ionospheric radio waves. Reconstruction of ionospheric electron density profiles with global navigation satellite system (GNSS) observations has become an indispensable technique for various purposes ranging from space physics studies to radio applications. This paper conducts a comprehensive review on the development of voxel-based computerized ionospheric tomography (CIT) in the last 30 years. A brief introduction is given in chronological order starting from the first report of CIT with simulation to the newly proposed voxel-based algorithms for ionospheric event analysis. The statement of the tomographic geometry and voxel models are outlined with the ill-posed and ill-conditioned nature of CIT addressed. With the additional information from other instrumental observations or initial models supplemented to make the coefficient matrix less ill-conditioned, equation constructions are categorized into constraints, virtual data assimilation and multi-source observation fusion. Then, the paper classifies and assesses the voxel-based CIT algorithms of the algebraic method, statistical approach and artificial neural networks for equation solving or electron density estimation. The advantages and limitations of the algorithms are also pointed out. Moreover, the paper illustrates the representative height profiles and two-dimensional images of ionospheric electron densities from CIT. Ionospheric disturbances studied with CIT are presented. It also demonstrates how the CIT benefits ionospheric correction and ionospheric monitoring. Finally, some suggestions are provided for further research about voxel-based CIT.

show abstract

Section: Singular Value Decompositionmentioning

confidence: 99%

A Review of Voxel-Based Computerized Ionospheric Tomography with GNSS Ground Receivers

Wan

2021

Remote Sensing

Self Cite

View full text Add to dashboard Cite

show abstract

“…To adequately solve Equation 8, the singular value decomposition (SVD) method was selected because of its numerically stable properties (Fan & Ma, 2014). The major disadvantage of SVD is the high computation cost; however, because the problem is transformed into EOF space, and the reconstructions are limited to the E region, the dimensionality of the problem is significantly reduced to a desktop CPU manageable setting.…”

Section: 𝐴𝐴 ⃖ ⃗ 𝑏𝑏 𝑡𝑡 𝑒𝑒mentioning

confidence: 99%

High‐Resolution 3‐D Imaging of Daytime Sporadic‐E Over Japan by Using GNSS TEC and Ionosondes

Ssessanga

Yokoyama

et al. 2021

Space Weather

View full text Add to dashboard Cite

Sporadic-E (E s ) are electron density inhomogeneities manifested in the ionospheric E region. At midlatitude area, during the daytime, E s is suggested to occur due to reinforced metallic (of meteoric origin) ionization in altitude range ∼95-120 km (Whitehead, 1989). Occasionally, E s becomes denser than the normal E-and F-layer densities, exhibiting a high correlation of occurrence with intense transionospheric signal scintillation (Maeda & Heki, 2014). Consequently, to forecast and draw patterns in the scintillation morphology, the space weather community has extensively investigated the E s structure both theoretically and experimentally. For example, information on the horizontal structures of midlatitude E s has been inferred by using ionosondes (Whitehead, 1972), radars (Miller & Smith, 1975), and rockets (Yamamoto et al., 1998. More so, S. Saito et al. ( 2006) obtained three-dimensional (3-D) structures of E s patches by using the middle and upper atmosphere (MU) radar at Shigaraki, Japan. Wu et al. (2005) deduced occurrence rates and intensities of E s at summertime midlatitudes, by using radio occultation measurements around the globe. Haldoupis (2011) and references therein have discussed an excellent tutorial review that summarizes the results from most of these studies and their affirmation on the E s structure. The literature suggests that the occurrence of E s varies with local time, altitude, latitude, longitude, and seasons, and its existence depends on the tidal wind, the Earth's geomagnetic field, and the level of meteoric depositions (Whitehead, 1989). Even with such rich literature, the E s generating mechanisms are not fully understood, although the wind shear theory driven by zonal winds has widely been accepted for the E s

show abstract

“…The polarity inversion of the pseudo‐random spreading code sequence can be considered to be random [16]. During the coherent integration time

T_{coh}

, the accumulated value

\sum_{n = 0}^{{\overset{false~}{N}}_{c} - 1} (\sum c \overset{false~}{c} ()(, n))

of the reference waveform satisfies the binomial distribution, and the variance can be expressed as

\begin{matrix} right leftthickmathspace.5em \\ VAR & = \frac{\bar{N}}{4} \\ = \frac{F_{normalc} T_{coh} \cdot |c_{normals} - 2 \cdot round (c_{normals} / 2)|}{4} \end{matrix}

Among them, the probability of a single event is equal to 1/2 and the total number of events is

F_{c} T_{coh} \cdot (||, c_{s} - 2 \cdot round ()(, c_{s} / 2))

.…”

Section: Statistical Characteristics Of Zero Biasmentioning

confidence: 99%

Zero‐bias elimination with selective non‐commensurate sampling for PN code tracking

Tang

et al. 2020

IET Radar, Sonar & Navigation

View full text Add to dashboard Cite

Characteristics of GPS positioning error with non-uniform pseudorange error

Cited by 10 publications

References 10 publications

A Review of Voxel-Based Computerized Ionospheric Tomography with GNSS Ground Receivers

A Review of Voxel-Based Computerized Ionospheric Tomography with GNSS Ground Receivers

High‐Resolution 3‐D Imaging of Daytime Sporadic‐E Over Japan by Using GNSS TEC and Ionosondes

Zero‐bias elimination with selective non‐commensurate sampling for PN code tracking

Contact Info

Product

Resources

About