Direct Position Estimation of GNSS Receivers: Analyzing main results, architectures, enhancements, and challenges

Closas, Pau; Gusi-Amigó, Adrià

doi:10.1109/msp.2017.2718040

Cited by 48 publications

(25 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…2) Model of Measurements Algorithms can be classified by the extractable positionrelated information, for example, signal power, carrier phase and symbol delay [19], [20]. They can also be classified according to the measurement abstraction level, whether to utilize the received waveform directly for localization, for example in direct position estimation (DPE) [21], or an abstracted single value metric with an associated likelihood function. For the latter case, algorithms can be further classified by the metrics extracted from the position-related information, such as time of arrival (ToA), time difference of arrival (TDoA), angle of arrival (AoA), received signal strength (RSS) [20], [22].…”

Section: ) Place Of Position Estimationmentioning

confidence: 99%

Distributed Direct Localization Suitable for Dense Networks

Zhang

Staudinger

Jost

et al. 2020

IEEE Trans. Aerosp. Electron. Syst.

View full text Add to dashboard Cite

Traditional network localization algorithms contain ranging and localization steps, which have systematic disadvantages. We propose an algorithm dubbed direct particle filter based distributed network localization (DiPNet). A node's location is directly estimated from the received signals, incorporating location uncertainty of neighboring nodes. The propagation effects on DiPNet become insignificant for dense networks, due to the massive-link collective physical layer processing. DiPNet achieves a near-optimal performance with low complexity, which is particularly attractive for realtime dense-network localization.

show abstract

Section: ) Place Of Position Estimationmentioning

confidence: 99%

Distributed Direct Localization Suitable for Dense Networks

Zhang

Staudinger

Jost

et al. 2020

IEEE Trans. Aerosp. Electron. Syst.

View full text Add to dashboard Cite

show abstract

“…Instead, DPE uses the maximum likelihood estimation (MLE) to directly estimate navigation solutions in the PVT domain [13,16]. DPE facilitates a deep coupling of the signals from different satellites, increases the effective signal power [14,15], and utilizes weak signals that would have otherwise been discarded [7,17].…”

Section: Related Workmentioning

confidence: 99%

GPS Multireceiver Direct Position Estimation for Aerial Applications

Chu

Chauhan

Gao

2020

IEEE Trans. Aerosp. Electron. Syst.

View full text Add to dashboard Cite

Modern aviation safety increasingly depends on reliable GPS services, while signal degrading effects such as multipath and masking often occur during critical flight phases, such as take-off and landing. In this regard, we propose Multi-Receiver Direct Position Estimation (MR-DPE), which operates a network of DPE receivers to enhance GPS measurement certainty in degraded signal environments. A DPE receiver directly estimates navigation solutions in the PVT domain with a maximum-likelihood approach, bypassing the intermediate range measurements. Whereas prior works have shown the enhanced measurement certainty of DPE under weak signals, MR-DPE provides further improvement by leveraging the information redundancy and the geometric diversity provided by the network of receivers and antennas. We implemented MR-DPE using software-defined radio and conducted comprehensive, full-scale flight experiments, a first for DPE-related works. A wide range of flight profiles were explored, especially those prone to signal multipath and masking, and preliminary analyses were performed on the data collected to ensure the conceptual validity of MR-DPE.ii To my parents, for their grace and character.iii ACKNOWLEDGMENTS

show abstract

“…These two stages, i.e., acquisition and tracking, can be seen as particular instances of the Maximum Likelihood (ML) solution. The optimal positioning solution is the so-called Direct Position Estimation (DPE) [7,8], that is, the direct ML position estimation from the sum of signals to all visible satellites. Indeed, the set of time-delays and Doppler shifts to each individual satellite are related to the same receiver position; thus, not exploiting them together is suboptimal because we are not taking into account the geometry constraint.…”

Section: Introductionmentioning

confidence: 99%

Performance Limits of GNSS Code-Based Precise Positioning: GPS, Galileo & Meta-Signals

Das

Ortega²,

Vilà‐Valls

et al. 2020

Sensors

View full text Add to dashboard Cite

This contribution analyzes the fundamental performance limits of traditional two-step Global Navigation Satellite System (GNSS) receiver architectures, which are directly linked to the achievable time-delay estimation performance. In turn, this is related to the GNSS baseband signal resolution, i.e., bandwidth, modulation, autocorrelation function, and the receiver sampling rate. To provide a comprehensive analysis of standard point positioning techniques, we consider the different GPS and Galileo signals available, as well as the signal combinations arising in the so-called GNSS meta-signal paradigm. The goal is to determine: (i) the ultimate achievable performance of GNSS code-based positioning systems; and (ii) whether we can obtain a GNSS code-only precise positioning solution and under which conditions. In this article, we provide clear answers to such fundamental questions, leveraging on the analysis of the Cramér–Rao bound (CRB) and the corresponding Maximum Likelihood Estimator (MLE). To determine such performance limits, we assume no external ionospheric, tropospheric, orbital, clock, or multipath-induced errors. The time-delay CRB and the corresponding MLE are obtained for the GPS L1 C/A, L1C, and L5 signals; the Galileo E1 OS, E6B, E5b-I, and E5 signals; and the Galileo E5b-E6 and E5a-E6 meta-signals. The results show that AltBOC-type signals (Galileo E5 and meta-signals) can be used for code-based precise positioning, being a promising real-time alternative to carrier phase-based techniques.

show abstract

Direct Position Estimation of GNSS Receivers: Analyzing main results, architectures, enhancements, and challenges

Cited by 48 publications

References 24 publications

Distributed Direct Localization Suitable for Dense Networks

Distributed Direct Localization Suitable for Dense Networks

GPS Multireceiver Direct Position Estimation for Aerial Applications

Performance Limits of GNSS Code-Based Precise Positioning: GPS, Galileo & Meta-Signals

Contact Info

Product

Resources

About