The GPS Assimilator: a Method for Upgrading Existing GPS User Equipment to Improve Accuracy, Robustness, and Resistance to Spoofing

Preprint of the 2010 ION GNSS Conference Portland, OR, September 21–24, 2010A conceptual method is presented for upgrading existing GPS user equipment, without requiring hardware or software modifications to the equipment, to improve the equipment’s position, velocity, and time (PVT) accuracy, to increase its PVT robustness in weak-signal or jammed environments, and to protect the equipment from counterfeit GPS signals (GPS spoofing). The method is embodied in a device called the GPS Assimilator that couples to the radio frequency (RF) input of an existing GPS receiver. The Assimilator extracts navigation and timing information from RF signals in its environment—including non-GNSS signals—and from direct baseband aiding provided, for example, by an inertial navigation system, a frequency reference, or the GPS user. The Assimilator optimally fuses the collective navigation and timing information to produce a PVT solution which, by virtue of the diverse navigation and timing sources on which it is based, is highly accurate and inherently robust to GPS signal obstruction and jamming. The Assimilator embeds the PVT solution in a synthesized set of GPS signals and injects these into the RF input of a target GPS receiver for which an accurate and robust PVT solution is desired. A prototype software-defined Assimilator device is presented with three example applications.Aerospace Engineerin

Collaborative navigation as a solution for PNT applications in GNSS challenged environments: report on field trials of a joint FIG / IAG working group

PNT stands for Positioning, Navigation, and Timing. Space-based PNT refers to the capabilities enabled by GNSS, and enhanced by Ground and Space-based Augmentation Systems (GBAS and SBAS), which provide position, velocity, and timing information to an unlimited number of users around the world, allowing every user to operate in the same reference system and timing standard. Such information has become increasingly critical to the security, safety, prosperity, and overall qualityof-life of many citizens. As a result, space-based PNT is now widely recognized as an essential element of the global information infrastructure. This paper discusses the importance of the availability and continuity of PNT information, whose application, scope and significance have exploded in the past 10–15 years. A paradigm shift in the navigation solution has been observed in recent years. It has been manifested by an evolution from traditional single sensor-based solutions, to multiple sensor-based solutions and ultimately to collaborative navigation and layered sensing, using non-traditional sensors and techniques – so called signals of opportunity. A joint working group under the auspices of the International Federation of Surveyors (FIG) and the International Association of Geodesy (IAG), entitled ‘Ubiquitous Positioning Systems’ investigated the use of Collaborative Positioning (CP) through several field trials over the past four years. In this paper, the concept of CP is discussed in detail and selected results of these experiments are presented. It is demonstrated here, that CP is a viable solution if a ‘network’ or ‘neighbourhood’ of users is to be positioned / navigated together, as it increases the accuracy, integrity, availability, and continuity of the PNT information for all users

Analysis of Multipath Mitigation Techniques with Land Mobile Satellite Channel Model

Multipath is undesirable for Global Navigation Satellite System (GNSS) receivers, since the reception of multipath can create a significant distortion to the shape of the correlation function leading to an error in the receivers’ position estimate. Many multipath mitigation techniques exist in the literature to deal with the multipath propagation problem in the context of GNSS. The multipath studies in the literature are often based on optimistic assumptions, for example, assuming a static two-path channel or a fading channel with a Rayleigh or a Nakagami distribution. But, in reality, there are a lot of channel modeling issues, for example, satellite-to-user geometry, variable number of paths, variable path delays and gains, Non Line-Of-Sight (NLOS) path condition, receiver movements, etc. that are kept out of consideration when analyzing the performance of these techniques. Therefore, this is of utmost importance to analyze the performance of different multipath mitigation techniques in some realistic measurement-based channel models, for example, the Land Multipath is undesirable for Global Navigation Satellite System (GNSS) receivers, since the reception of multipath can create a significant distortion to the shape of the correlation function leading to an error in the receivers’ position estimate. Many multipath mitigation techniques exist in the literature to deal with the multipath propagation problem in the context of GNSS. The multipath studies in the literature are often based on optimistic assumptions, for example, assuming a static two-path channel or a fading channel with a Rayleigh or a Nakagami distribution. But, in reality, there are a lot of channel modeling issues, for example, satellite-to-user geometry, variable number of paths, variable path delays and gains, Non Line-Of-Sight (NLOS) path condition, receiver movements, etc. that are kept out of consideration when analyzing the performance of these techniques. Therefore, this is of utmost importance to analyze the performance of different multipath mitigation techniques in some realistic measurement-based channel models, for example, the Land Mobile Satellite (LMS) channel model [1]-[4], developed at the German Aerospace Center (DLR). The DLR LMS channel model is widely used for simulating the positioning accuracy of mobile satellite navigation receivers in urban outdoor scenarios. The main objective of this paper is to present a comprehensive analysis of some of the most promising techniques with the DLR LMS channel model in varying multipath scenarios. Four multipath mitigation techniques are chosen herein for performance comparison, namely, the narrow Early-Minus-Late (nEML), the High Resolution Correlator, the C/N0-based two stage delay tracking technique, and the Reduced Search Space Maximum Likelihood (RSSML) delay estimator. The first two techniques are the most popular and traditional ones used in nowadays GNSS receivers, whereas the later two techniques are comparatively new and are advanced techniques, recently proposed by the authors. In addition, the implementation of the RSSML is optimized here for a narrow-bandwidth receiver configuration in the sense that it now requires a significantly less number of correlators and memory than its original implementation. The simulation results show that the reduced-complexity RSSML achieves the best multipath mitigation performance in moderate-to-good carrier-to-noise density ratio with the DLR LMS channel model in varying multipath scenarios

A tripartite filter design for seamless pedestrian navigation using recursive 2-means clustering and Tukey update

Mobile devices are desired to guide users seamlessly to diverse destinations indoors and outdoors. The positioning fixing subsystems often provide poor quality measurements with gaps in an urban environment. No single position fixing technology works continuously. Many sensor fusion variations have been previously trialed to overcome this challenge, including the particle filter that is robust and the Kalman filter which is fast. However, a lack exists, of context aware, seamless systems that are able to use the most fit sensors and methods in the correct context. A novel adaptive and modular tripartite navigation filter design is presented to enable seamless navigation. It consists of a sensor subsystem, a context inference and a navigation filter blocks. A foot-mounted inertial measurement unit (IMU), a Global Navigation Satellite System (GNSS) receiver, Bluetooth Low Energy (BLE) and Ultrawideband (UWB) positioning systems were used in the evaluation implementation of this design. A novel recursive 2-means clustering method was developed to track multiple hypotheses when there are gaps in position fixes. The closest hypothesis to a new position fix is selected when the gap ends. Moreover, when the position fix quality measure is not reliable, a fusion approach using a Tukey-style particle filter measurement update is introduced. Results show the successful operation of the design implementation. The Tukey update improves accuracy by 5% and together with the clustering method the system robustness is enhanced

Infrared ranging in multipath environments for indoor localization of mobile targets

Esta tesis aborda el problema de la medida de diferencias de distancia mediante señales ópticas afectadas por multicamino, aplicada a la localización de agentes móviles en espacios interiores. Los avances en robótica, entornos inteligentes y vehículos autónomos han creado un campo de aplicación específico para la localización en interiores, cuyos requerimientos de precisión (en el rango de los cm) son muy superiores a los demandados por las aplicaciones de localización orientadas a personas, en cuyo contexto se han desarrollado la mayor parte de las alternativas tecnológicas. La investigación con métodos de geometría proyectiva basados en cámaras y de multilateración basados en medida de distancia con señales de radiofrecuencia de banda ancha, de ultrasonido y ópticas han demostrado un rendimiento potencial adecuado para cubrir estos requerimientos. Sin embargo, todas estas alternativas, aún en fase de investigación, presentan dificultades que limitan su aplicación práctica. En el caso de los sistemas ópticos, escasamente estudiados en este contexto, los trabajos previos se han basado en medidas de diferencia de fase de llegada de señales infrarrojas moduladas sinusoidalmente en intensidad. Una infraestructura centralizada computa medidas diferenciales, entre receptores fijos, de la señal emitida desde el móvil a posicionar, y calcula la posición del móvil mediante trilateración hiperbólica a partir de éstas. Estas investigaciones demostraron que se pueden alcanzar precisiones de pocos centímetros; sin embargo, las interferencias por multicamino debidas a la reflexión de la señal óptica en superficies del entorno pueden degradar esta precisión hasta las decenas de centímetros dependiendo de las características del espacio. Así pues, el efecto del multicamino es actualmente la principal fuente de error en esta tecnología, y por tanto, la principal barrera a superar para su implementación en situaciones reales. En esta tesis se propone y analiza un sistema de medida con señales ópticas que permite obtener estimaciones de diferencias de distancia precisas reduciendo el efecto crítico del multicamino. El sistema propuesto introduce una modulación con secuencias de ruido pseudoaleatorio sobre la modulación sinusoidal típicamente usada para medida de fase por onda continua, y aprovecha las propiedades de ensanchamiento en frecuencia de estas secuencias para reducir el efecto del multicamino. El sistema, que realiza una doble estimación de tiempo y fase de llegada, está compuesto por una etapa de sincronización que posibilita la demodulación parcialmente coherente de la señal recibida, seguida de un medidor diferencial de fase sobre las componentes desensanchadas tras la demodulación. Las condiciones de multicamino óptico típicas en espacios interiores, con una componente de camino directo claramente dominante, permiten que el proceso de demodulación recupere más potencia del camino directo que del resto de contribuciones, reduciendo el efecto del multicamino en la estimación final. Los resultados obtenidos demuestran que la aplicación del método propuesto permitiría realizar posicionamiento a partir de señales ópticas con el rendimiento adecuando para aplicaciones de robótica y guiado de vehículos en espacios interiores; además, el progresivo aumento de la potencia y el ancho de banda de los dispositivos optoelectrónicos disponibles permite esperar un incremento considerable de las prestaciones de la propuesta en los próximos años

Indoor Positioning Trends in 5G-Advanced: Challenges and Solution towards Centimeter-level Accuracy

After robust connectivity, precise positioning is evolving into an innovative component of 5G service offerings for industrial use-cases and verticals with challenging indoor radio environments. In this direction, the 3GPP Rel-16 standard has been a tipping point in specifying critical innovations, followed by enhancements in Rel-17+. In this article, we follow this path to elaborate on the 5G positioning framework, measurements, and methods before shifting the focus to carrier-phase (CP) measurements as a complementary measure for time- and angular-based positioning methods toward achieving centimeter-level accuracy. As this path is not without challenges, we discuss these and outline potential solutions. As an example of solutions, we study how phase-continuous reference signaling can counter noisy phase measurements using realistic simulations in an indoor factory (InF) scenario.Comment: 5 figures, 1 table, under review for possible publication in IEEE Communications Magazin

Grid-based Hybrid 3DMA GNSS and Terrestrial Positioning

The paper discusses the increasing use of hybridized sensor information for GNSS-based localization and navigation, including the use of 3D map-aided GNSS positioning and terrestrial systems based on different geometric measurement principles. However, both GNSS and terrestrial systems are subject to negative impacts from the propagation environment, which can violate the assumptions of conventionally applied parametric state estimators. Furthermore, dynamic parametric state estimation does not account for multi-modalities within the state space leading to an information loss within the prediction step. In addition, the synchronization of non-deterministic multi-rate measurement systems needs to be accounted. In order to address these challenges, the paper proposes the use of a non-parametric filtering method, specifically a 3DMA multi-epoch Grid Filter, for the tight integration of GNSS and terrestrial signals. Specifically, the fusion of GNSS, Ultra-wide Band (UWB) and vehicle motion data is introduced based on a discrete state representation. Algorithmic challenges, including the use of different measurement models and time synchronization, are addressed. In order to evaluate the proposed method, real-world tests were conducted on an urban automotive testbed in both static and dynamic scenarios. We empirically show that we achieve sub-meter accuracy in the static scenario by averaging a positioning error of $0.64$ m, whereas in the dynamic scenario the average positioning error amounts to $1.62$ m. The paper provides a proof-of-concept of the introduced method and shows the feasibility of the inclusion of terrestrial signals in a 3DMA positioning framework in order to further enhance localization in GNSS-degraded environments

Neural Network-Based Ranging with LTE Channel Impulse Response for Localization in Indoor Environments

A neural network (NN)-based approach for indoor localization via cellular long-term evolution (LTE) signals is proposed. The approach estimates, from the channel impulse response (CIR), the range between an LTE eNodeB and a receiver. A software-defined radio (SDR) extracts the CIR, which is fed to a long short-term memory model (LSTM) recurrent neural network (RNN) to estimate the range. Experimental results are presented comparing the proposed approach against a baseline RNN without LSTM. The results show a receiver navigating for 100 m in an indoor environment, while receiving signals from one LTE eNodeB. The ranging root-mean squared error (RMSE) and ranging maximum error along the receiver's trajectory were reduced from 13.11 m and 55.68 m, respectively, in the baseline RNN to 9.02 m and 27.40 m, respectively, with the proposed RNN-LSTM.Comment: Submitted to ICCAS 202