2026· Materials Research Proceedings· Vol 69, pp. 42-47· 0 citations
TL;DR
An approach is proposed to improve accuracy through adaptive weighting strategies and multipath isolation techniques and this strategy is combined with a multipath detection technique using the Code-minus-carrier (CMC) rate of change.
Abstract
Abstract. This work addresses the challenge of multipath interference in Global Navigation Satellite System (GNSS) positioning. An approach is proposed to improve accuracy through adaptive weighting strategies and multipath isolation techniques. Weighting methods based on elevation and carrier-to-noise ratio (C/N0) are employed, and this strategy is combined with a multipath detection technique using the Code-minus-carrier (CMC) rate of change. The method is tested using a Piksi Multi GNSS Module, with data processed using Standard Point Positioning (SPP) techniques. An 8-state filter based on a Position-Velocity (PV) model is implemented for dynamic state estimation. Experiments in static and dynamic scenarios demonstrate significant improvements in positioning accuracy.
This study explores methods for precise attitude estimation using carrier phases within global positioning systems (GPS). Carrier phase data is preferred over pseudorange data for short baseline distances due to its lower noise levels. However, resolving ambiguities through integer ambiguity resolution methods is essential for effectively utilizing carrier phases. One widely adopted approach, the LAMBDA method, is introduced, alongside a solution tailored for low-cost GPS systems and receivers with higher error. The novel method primarily focuses on utilizing only the fractional parts of the carrier phases while integrating constraints such as pitch and baseline constraints to enhance ambiguity detection accuracy. Comparative analysis with the LAMBDA approach demonstrates that the proposed method achieves remarkable accuracy, even in environments characterized by multipath interference.
Habib Kanberoğlu, Mukaddes Bolat· Tehnički glasnik· 0 citations
Global Navigation Satellite Systems (GNSS) are widely used in intelligent transportation systems (ITS) and autonomous driving. However, in urban canyons and tunnels, multipath, blockage, and interference reduce SNR and degrade positioning accuracy. This paper proposes a high-SNR GNSS receiver architecture based on RF front-end optimization. The design integrates a low-noise amplifier (LNA), a high-linearity mixer, and an adaptive automatic gain control (AGC) mechanism within a jointly optimized RF front-end architecture, aiming to improve signal quality at the receiver input under weak-signal conditions. Experimental results show an SNR improvement of approximately 6 dB compared with a conventional receiver, along with improved positioning accuracy under both open-sky and weak-signal conditions.
Zimu Zhou, Ran Li, Zhi Li et al.· Journal of Physics, Conferen...· 0 citations
Accurate positioning of Global Navigation Satellite System (GNSS) is essential for civil applications but degrades in harsh environments, especially in vegetated environments. While building impacts on GNSS performance are well-studied, vegetation effects remain poorly characterized. Although existing studies have analyzed observation-level behaviors like positioning errors, their underlying causes remain unclear. This study investigates GNSS performance in vegetated environments through observation- and signal-level analyses. Vegetation-induced attenuation alters GNSS signal strength patterns, rendering conventional positioning strategies ineffective. Signal-level analysis using intermediate-frequency (IF) data and maximum likelihood multipath estimators reveals distinctive external multipath characteristics and internal scattering effects under vegetation. Tracking error analysis further shows error distributions under vegetation that differ from those in nonvegetation environments. Based on these findings, the extension of the existing positioning method to perform adaptive positioning is explored, demonstrating the potential benefits of incorporating vegetation effects to improve GNSS positioning accuracy.
Di Hai, Chin Lok Tsang, Guohao Zhang· IEEE Transactions on Instrum...· 0 citations
In two-station 3-D passive source localization, combined angle of arrival (AOA) and time difference of arrival (TDOA) methods often exhibit performance degradation at low signal-to-noise ratios (SNRs). To address this issue, this letter first derives an error propagation model and demonstrates the limitations of the conventional algorithm. Based on this basis, we develop a two-station constrained weighted total least squares (CWTLS) estimator that accurately accounts for noise in both the measurement and the coefficient matrix. Simulations and field experiments show that, compared to the traditional weighted least squares (WLS) algorithm, the proposed method reduces bias by 75% under low SNR and achieves localization accuracy that is closer to the Cramér–Rao bound (CRB) across different geometric configurations.
Global Navigation Satellite Systems (GNSS) provide essential positioning, navigation, and timing (PNT) services for a wide range of safety-critical applications. However, GNSS performance degrades significantly in satellite-deficient or interference-prone environments. To address this limitation, this study proposes a hybrid GNSS/eLoran integrity monitoring framework based on a simplified Receiver Autonomous Integrity Monitoring (RAIM) architecture. In the proposed method, GNSS observations from satellite constellations and range-equivalent measurements from the enhanced Loran (eLoran) terrestrial system are jointly processed using a weighted least-squares estimator. Integrity monitoring is performed through a global chi-square consistency test combined with a solution separation strategy for fault identification and exclusion. Horizontal Protection Level (HPL) is derived from the covariance of the estimation process to ensure bounded positioning error under nominal and fault conditions. Unlike conventional GNSS-only RAIM, the proposed framework enables improved redundancy and fault observability in satellite-deficient scenarios by incorporating heterogeneous terrestrial measurements. Simulation experiments consider satellite faults, eLoran measurement disturbances, and inter-system clock bias effects. Results demonstrate that the proposed method maintains reliable fault detection capability and ensures that positioning errors remain consistently bounded by the protection level under all tested scenarios.
Jingling Li, Huabing Wu· Italian National Conference...· 0 citations
(English) Achieving robust positioning across ground and UAV platforms remains challenging under multipath, partial satellite visibility, and rapidly changing measurement quality, especially in urban and embedded scenarios. At the same time, modern smartphones and embedded receivers increasingly provide multi-constellation, dual-frequency observations, carrier-phase measurements, and IMU streams that can be exploited for aided positioning.
The present thesis addresses these conditions through a robust GNSS/IMU integration framework, evaluated across heterogeneous sensor grades, from navigation-grade platforms to consumer smartphones. The framework is designed not only for offline post-processing, but also for real-time and embedded operation, following a deterministic execution structure suitable for on-board use.
The principal conclusions are:
First, a unified processing framework has been developed for GNSS/IMU integration using raw, undifferenced, uncombined GNSS observables (code, carrier phase, Doppler) and inertial measurements.
Second, a Square-Root Information Filter (SRIF) architecture has been adopted as the estimator core, enabling a numerically robust implementation and a shared software structure across GNSS-only processing, loosely coupled (LC) fusion, and tightly coupled (TC) fusion modes.
Third, Allan deviation analysis has been used systematically to identify inertial noise parameters and to configure the process-noise model of the navigation filter across different IMU classes, improving consistency of tuning when detailed manufacturer specifications are incomplete.
Fourth, experimental validation on multiple independent datasets, spanning different GNSS conditions and equipment grades, shows that LC fusion provides the most consistent practical gains, especially in continuity and robustness during short GNSS degradations, and often improves typical solution behaviour when inertial data quality is adequate.
Fifth, in dense urban conditions with strong multipath and masking, positioning performance remains fundamentally constrained by GNSS measurement quality and correction level; inertial aiding mitigates short-term disruptions but does not eliminate the GNSS-side error ceiling.
Finally, the thesis demonstrates a transferable and numerically stable GNSS/IMU integration framework, a reproducible Allan-based methodology for configuring heterogeneous IMUs in the filter, and a realistic path toward robust positioning under practical field conditions.
(Català) Assolir un posicionament robust en plataformes terrestres i UAV continua sent un repte en presencia de multipath, visibilitat satel·lital parcial i canvis rapids en la qualitat de les observacions, especialment en escenaris urbans i embeguts. Al mateix temps, els telefons intel·ligents i els receptors embeguts moderns proporcionen cada cop mes observacions multiconstel·lacio i de doble frequencia, mesures de fase portadora i fluxos IMU aprofitables per al posicionament assistit.
La present tesi aborda aquestes condicions mitjancant un marc robust d'integracio GNSS/IMU, avaluat en sensors de diferents graus, des de plataformes de grau de navegacio fins a telefons intel·ligents de consum.
El marc esta concebut no nomes per al post-processament fora de linia, sino tambe per a operacio en temps real i en sistemes encastats, seguint una estructura d'execucio determinista adequada per a aquest tipus de desplegament.
Les conclusions de la recerca son:
Primer, s'ha desenvolupat un marc unificat de processament per a la integracio GNSS/IMU utilitzant observables GNSS crus, no diferenciats i no combinats (codi, fase portadora i Doppler) i mesures inercials.
Segon, s'ha adoptat una arquitectura de Filtre d'Informacio en Arrel Quadrada (SRIF) com a nucli de l'estimador, la qual cosa permet una implementacio numericament robusta i una estructura de programari compartida per al processament GNSS-only, la fusio en acoblament lax (LC) i la fusio en acoblament estret (TC).
Tercer, l'analisi de desviacio d'Allan s'ha utilitzat de manera sistematica per identificar parametres de soroll inercial i per configurar el model de soroll de proces del filtre de navegacio en diferents classes d'IMU, millorant la coherencia de l'ajust quan les especificacions del fabricant son incompletes.
Quart, la validacio experimental en multiples conjunts de dades independents, que abasten diferents condicions GNSS i graus d'equipament, mostra que la fusio LC aporta les millores practiques mes consistents, especialment en continuitat i robustesa davant degradacions breus de GNSS, i sovint millora el comportament tipic de la solucio quan la qualitat de les dades inercials es adequada.
Cinque, en entorns urbans densos, amb multipath intens i emmascarament, el rendiment del posicionament continua limitat de manera fonamental per la qualitat de la mesura GNSS i el nivell de correccions; l'ajuda inercial mitiga interrupcions de curt termini, pero no elimina el sostre d'error del costat GNSS.
Finalment, en conjunt, la tesi demostra un marc d'integracio GNSS/IMU transferible i numericament estable, una metodologia reproduible basada en Allan per configurar IMUs heterogenis al filtre, i una via realista cap a un posicionament robust en condicions de camp.
(Español) Lograr un posicionamiento robusto en plataformas terrestres y UAV sigue siendo un reto en presencia de multitrayectoria, visibilidad satelital parcial y cambios rapidos en la calidad de las observaciones, especialmente en escenarios urbanos y embebidos. Al mismo tiempo, los telefonos inteligentes y receptores embebidos modernos proporcionan cada vez mas observaciones multiconstelacion y de doble frecuencia, medidas de fase portadora y flujos IMU aprovechables para posicionamiento asistido.
La presente tesis aborda estas condiciones mediante un marco robusto de integracion GNSS/IMU, evaluado en sensores de distintos grados, desde plataformas de grado navegacion hasta telefonos inteligentes de consumo. El marco esta concebido no solo para post-procesado fuera de linea, sino tambien para operacion en tiempo real y en sistemas embebidos, siguiendo una estructura de ejecucion determinista adecuada para uso a bordo.
Las principales conclusiones son:
Primero, se ha desarrollado un marco unificado de procesamiento para la integracion GNSS/IMU utilizando observables GNSS brutos, no diferenciados y no combinados (codigo, fase portadora y Doppler) y medidas inerciales.
Segundo, se ha adoptado una arquitectura de Filtro de Informacion en Raiz Cuadrada (SRIF) como nucleo del estimador, lo que permite una implementacion numericamente robusta y una estructura software compartida para el procesamiento GNSS-only, la fusion en acoplamiento laxo (LC) y la fusion en acoplamiento estrecho (TC).
Tercero, el analisis de desviacion de Allan se ha utilizado de forma sistematica para identificar parametros de ruido inercial y para configurar el modelo de ruido de proceso del filtro de navegacion en distintas clases de IMU, mejorando la coherencia del ajuste cuando las especificaciones del fabricante son incompletas.
Cuarto, la validacion experimental en multiples conjuntos de datos independientes, que abarcan distintas condiciones GNSS y grados de equipamiento, muestra que la fusion LC aporta las mejoras practicas mas consistentes, especialmente en continuidad y robustez ante degradaciones breves de GNSS, y a menudo mejora el comportamiento tipico de la solucion cuando la calidad de los datos inerciales es adecuada.
Quinto, en entornos urbanos densos, con multipath intenso y enmascaramiento, el rendimiento del posicionamiento sigue limitado de forma fundamental por la calidad de la medida GNSS y el nivel de correcciones; la ayuda inercial mitiga interrupciones de corto plazo, pero no elimina el techo de error del lado GNSS.
Por ultimo, en conjunto, la tesis demuestra un marco de integracion GNSS/IMU transferible y numericamente estable, una metodologia reproducible basada en Allan para configurar IMUs heterogeneos en el filtro, y una via realista hacia un posicionamiento robusto en condiciones de campo.