An Assessment of Impact of Adaptive Notch Filters for Interference Removal on the Signal Processing Stages of a GNSS Receiver

With the fast growing diffusion of the real-time high accuracy applications based on the Global Navigation Satellite System (GNSS), the robustness of the GNSS receiver performance has become a compelling requirement. Disruptive effects can be induced to the signal processing stages of GNSS receivers due to the disturbances from Radio-Frequency Interference (RFI), even leading to a complete outage of the positioning and timing service. A typical RFI threat to the GNSS signals is represented by portable jammers which transmit swept-frequency (chirp) signals in order to span the overall GNSS bandwidth. The implementation in the receivers of Adaptive Notch Filters (ANFs) for chirp cancellation has been extensively investigated and proved to be an efficient countermeasure. However, the performance of ANF is strongly dependent on its configuration setup. Inappropriate parameter settings of the ANF for interference removal may induce severe distortion to the correlation process. In addition, an effective mitigation will still introduce a vestigial signal distortion contributed by the residual unmitigated chirp and the ANF operation itself, being not negligible for high accuracy solutions. This paper addresses the detailed analysis for assessing the effects of interference mitigation by notch filtering. A bias compensation strategy is proposed, wherein for each Pseudo Random Noise (PRN) the biases due to the parameter settings of the notch filter are estimated and compensated. The impact of using the ANF operation on chirp signals at the acquisition and tracking stages of GNSS receivers is analyzed. On the basis of the three proposed metrics, the effects can be quantitatively estimated to depict a complete picture of the most influential parameters of the chirp and the ANF configurations, as well as the optimal achievable performance at the acquisition and tracking stages

GNSS Radio Frequency Interference Monitoring from LEO Satellites: An In-Laboratory Prototype

The disruptive effect of radio frequency interference (RFI) on global navigation satellite system (GNSS) signals is well known, and in the last four decades, many have been investigated as countermeasures. Recently, low-Earth orbit (LEO) satellites have been looked at as a good opportunity for GNSS RFI monitoring, and the last five years have seen the proliferation of many commercial and academic initiatives. In this context, this paper proposes a new spaceborne system to detect, classify, and localize terrestrial GNSS RFI signals, particularly jamming and spoofing, for civil use. This paper presents the implementation of the RFI detection software module to be hosted on a nanosatellite. The whole development work is described, including the selection of both the target platform and the algorithms, the implementation, the detection performance evaluation, and the computational load analysis. Two are the implemented RFI detectors: the chi-square goodness-of-fit (GoF) algorithm for non-GNSS-like interference, e.g., chirp jamming, and the snapshot acquisition for GNSS-like interference, e.g., spoofing. Preliminary testing results in the presence of jamming and spoofing signals reveal promising detection capability in terms of sensitivity and highlight room to optimize the computational load, particularly for the snapshot-acquisition-based RFI detector

Internet of Robotic Things Intelligent Connectivity and Platforms

The Internet of Things (IoT) and Industrial IoT (IIoT) have developed rapidly in the past few years, as both the Internet and “things” have evolved significantly. “Things” now range from simple Radio Frequency Identification (RFID) devices to smart wireless sensors, intelligent wireless sensors and actuators, robotic things, and autonomous vehicles operating in consumer, business, and industrial environments. The emergence of “intelligent things” (static or mobile) in collaborative autonomous fleets requires new architectures, connectivity paradigms, trustworthiness frameworks, and platforms for the integration of applications across different business and industrial domains. These new applications accelerate the development of autonomous system design paradigms and the proliferation of the Internet of Robotic Things (IoRT). In IoRT, collaborative robotic things can communicate with other things, learn autonomously, interact safely with the environment, humans and other things, and gain qualities like self-maintenance, self-awareness, self-healing, and fail-operational behavior. IoRT applications can make use of the individual, collaborative, and collective intelligence of robotic things, as well as information from the infrastructure and operating context to plan, implement and accomplish tasks under different environmental conditions and uncertainties. The continuous, real-time interaction with the environment makes perception, location, communication, cognition, computation, connectivity, propulsion, and integration of federated IoRT and digital platforms important components of new-generation IoRT applications. This paper reviews the taxonomy of the IoRT, emphasizing the IoRT intelligent connectivity, architectures, interoperability, and trustworthiness framework, and surveys the technologies that enable the application of the IoRT across different domains to perform missions more efficiently, productively, and completely. The aim is to provide a novel perspective on the IoRT that involves communication among robotic things and humans and highlights the convergence of several technologies and interactions between different taxonomies used in the literature.publishedVersio

Algorithmes et architectures pour ladétection des signaux MIMO

Multiple Input Multiple Output (MIMO) systems are recognized as a key enabling technology in high performance wireless communications. However the complexity of high throughput MIMO detectors poses a serious implementation issue. Among known MIMO detectors, Sphere Decoder Algorithm (SDA) has emerged to reduce the processing complexity, with respect to the original Maximum Likelihood (ML) detection. Moreover, it has been demonstrated that the SDA achieves optimal performance for uncoded systems. However, for coded systems, further simplifications in the detection algorithm can be used without altering the error rate performance if iterative detection and channel decoding is adopted in the receiver. Such an iterative processing with a channel decoder offers significant improvement in error-rate performance for a reduced signal-to-noise ratio. In this context, the SDA can be further simplified and modified in order to provide soft detection: ¿List Sphere Decoder¿ (LSD) has been introduced as a soft version of the original SDA. This research thesis focuses on algorithmic, architectural and implementation aspects of the ¿ Sphere Decoder Algorithm¿ and the ¿List Sphere Decoder¿. The main objective of the conducted work is to propose area-efficient implementation solutions while considering throughput, flexibility, and error rate performance requirements of advanced digital communication systems. In particular, the first contribution is represented by an improved SDA, which enables significant throughput increase at a very limited additional complexity and with no degradation in terms of Bit Error Rate performance. The proposed detection method, called LASDA (Look¿Ahead SDA) is based on formal algorithm transformations, namely look¿ahead, retiming and pipelining, besides a modified tree search strategy. An efficient VLSI design of LASDA detector supporting a 4x4 MIMO channel with 16QAM modulation is proposed. Synthesis results for a 130 nm technology are detailed. The second contribution concerns a detailed study on flexibility and convergence of iterative detection and channel decoding. In this regard, two Soft-Input Soft-Output detectors are considered: List Sphere Decoding and a low complexity linear filtering (Linear Minimum-Mean-Square-Error-Interference-Canceller (MMSE-IC)). Extrinsic Information Transfer (EXIT) charts are developed. This analysis is oriented to obtain possible performance-complexity trade-offs for a flexible hardware implementation. The last contribution is related to the proposal and design of an Application-Specific-Instruction set-Processor (ASIP) for SISO List Sphere Decoding. The proposed ASIP supports different MIMO system configurations (2x2, 3x3, 4x4) and modulation orders (QPSK, 16QAM, 64QAM) besides a flexible list size (from 1 to 64 elements). Synthesis results for a 130 nm technology are detailed.Les systèmes multi-antennes (Multiple-Input Multiple-Output: MIMO) représentent une technologie clé pour le déploiement de systèmes de communication sans fil. Cependant, la complexité des détecteurs MIMO de haut débit pose un problème sérieux de mise en oeuvre. Parmi les détecteurs MIMO existants, l'algorithme nommé détecteur à sphère (Sphere Decoder Algorithm: SDA) a vu le jour pour réduire la complexité de traitement par rapport à la technique de détection originale basée sur le maximum de vraisemblance (ML). En outre, il a été démontré que SDA atteint des performances optimales pour les systèmes non codés. Toutefois, pour les systèmes codés, d'autres simplifications dans l'algorithme de détection peuvent être utilisées sans altérer les performances en taux d'erreur. Dans ce contexte, le SDA peut être modifié afin de prévoir une détection basée sur des informations pondérées. LSD (List-Sphere Decoder) a été introduit comme une version à entrées/sorties pondérées de la version SDA originale. Ce travail de thèse traite les aspects algorithmique, architectural et de mise en oeuvre de la détection MIMO basée sur SDA et LSD. Le principal objectif est de proposer des solutions de mise en oeuvre de faible complexité, tout en considérant les exigences des systèmes de communication numérique en termes de débit, de flexibilité et de taux d'erreurs. En particulier, la première contribution est représentée par une amélioration de SDA, ce qui permet une augmentation significative du débit avec une complexité supplémentaire très limitée et sans dégradation en termes de performance en taux derreurs binaires. La méthode de détection proposée, appelée LASDA (Look-Ahead SDA), est basée sur des transformations formelles, à savoir Look-Ahead, recalage et pipeline et sur une stratégie modifiée de recherche arborescente. Une conception efficace de type VLSI du détecteur LASDA supportant un system MIMO 4x4 avec une modulation MAQ-16 est proposée. La deuxième contribution concerne une étude détaillée sur la flexibilité et la convergence de la détection itérative. Deux détecteurs à entrées/sorties pondérées (Soft-Input Soft-Output: SISO) sont considérés: LSD et un filtrage linéaire de faible complexité (Linear Minimum-Mean-Square-Error-Interference-Canceller (MMSE-IC)). Des diagrammes de transfert d'information mutuelle (EXIT charts) sont développés. Cette analyse est orientée pour obtenir les compromis possibles entre complexité et performance pour une implémentation matérielle flexible. La dernière contribution est liée à la conception d'un processeur à jeu d'instructions dédié à l'application (Application-Specific Instruction-set Processor (ASIP)) pour un détecteur SISO LSD. L'ASIP proposé supporte différentes configurations MIMO (2x2, 3x3, 4x4) et différents ordres de modulation (QPSK, MAQ-16, MAQ-64) en plus d'une taille de liste flexible (1 à 64 éléments)

Prototyping a GNSS-Based Passive Radar for UAVs: An Instrument to Classify the Water Content Feature of Lands

Global Navigation Satellite Systems (GNSS) broadcast signals for positioning and navigation, which can be also employed for remote sensing applications. Indeed, the satellites of any GNSS can be seen as synchronized sources of electromagnetic radiation, and specific processing of the signals reflected back from the ground can be used to estimate the geophysical properties of the Earth’s surface. Several experiments have successfully demonstrated GNSS-reflectometry (GNSS-R), whereas new applications are continuously emerging and are presently under development, either from static or dynamic platforms. GNSS-R can be implemented at a low cost, primarily if small devices are mounted on-board unmanned aerial vehicles (UAVs), which today can be equipped with several types of sensors for environmental monitoring. So far, many instruments for GNSS-R have followed the GNSS bistatic radar architecture and consisted of custom GNSS receivers, often requiring a personal computer and bulky systems to store large amounts of data. This paper presents the development of a GNSS-based sensor for UAVs and small manned aircraft, used to classify lands according to their soil water content. The paper provides details on the design of the major hardware and software components, as well as the description of the results obtained through field tests

Computational Load Analysis of a Galileo OSNMA-Ready Receiver for ARM-Based Embedded Platforms

Many GNSS applications have been experiencing some constantly growing needs in terms of security and reliability. To address some of them, both GPS and Galileo are proposing evolutions of their legacy civil signals, embedding features of authentication. This paper focuses on the Galileo Open Signal Navigation Message Authentication (OSNMA) and describes its implementation within a real-time software receiver for ARM-based embedded platforms. The innovative contributions of the paper include the software profiling analysis for the OSNMA add on, along with the comparison among performances obtained with different platforms. In addition, specific evaluations on the computational load of the whole receiver complete the analysis. The receiver used for the implementation belongs to the NGene receivers family—real-time fully-software GPS and Galileo receivers, tailored for different platforms and sharing the same core processing. In detail, the paper deals with the introduction of the OSNMA support inside the eNGene, the version of the receiver executable by ARM-based embedded platforms

Algorithmes et architectures pour ladétection des signaux MIMO

Multiple Input Multiple Output (MIMO) systems are recognized as a key enabling technology in high performance wireless communications. However the complexity of high throughput MIMO detectors poses a serious implementation issue. Among known MIMO detectors, Sphere Decoder Algorithm (SDA) has emerged to reduce the processing complexity, with respect to the original Maximum Likelihood (ML) detection. Moreover, it has been demonstrated that the SDA achieves optimal performance for uncoded systems. However, for coded systems, further simplifications in the detection algorithm can be used without altering the error rate performance if iterative detection and channel decoding is adopted in the receiver. Such an iterative processing with a channel decoder offers significant improvement in error-rate performance for a reduced signal-to-noise ratio. In this context, the SDA can be further simplified and modified in order to provide soft detection: ¿List Sphere Decoder¿ (LSD) has been introduced as a soft version of the original SDA. This research thesis focuses on algorithmic, architectural and implementation aspects of the ¿ Sphere Decoder Algorithm¿ and the ¿List Sphere Decoder¿. The main objective of the conducted work is to propose area-efficient implementation solutions while considering throughput, flexibility, and error rate performance requirements of advanced digital communication systems. In particular, the first contribution is represented by an improved SDA, which enables significant throughput increase at a very limited additional complexity and with no degradation in terms of Bit Error Rate performance. The proposed detection method, called LASDA (Look¿Ahead SDA) is based on formal algorithm transformations, namely look¿ahead, retiming and pipelining, besides a modified tree search strategy. An efficient VLSI design of LASDA detector supporting a 4x4 MIMO channel with 16QAM modulation is proposed. Synthesis results for a 130 nm technology are detailed. The second contribution concerns a detailed study on flexibility and convergence of iterative detection and channel decoding. In this regard, two Soft-Input Soft-Output detectors are considered: List Sphere Decoding and a low complexity linear filtering (Linear Minimum-Mean-Square-Error-Interference-Canceller (MMSE-IC)). Extrinsic Information Transfer (EXIT) charts are developed. This analysis is oriented to obtain possible performance-complexity trade-offs for a flexible hardware implementation. The last contribution is related to the proposal and design of an Application-Specific-Instruction set-Processor (ASIP) for SISO List Sphere Decoding. The proposed ASIP supports different MIMO system configurations (2x2, 3x3, 4x4) and modulation orders (QPSK, 16QAM, 64QAM) besides a flexible list size (from 1 to 64 elements). Synthesis results for a 130 nm technology are detailed.Les systèmes multi-antennes (Multiple-Input Multiple-Output: MIMO) représentent une technologie clé pour le déploiement de systèmes de communication sans fil. Cependant, la complexité des détecteurs MIMO de haut débit pose un problème sérieux de mise en oeuvre. Parmi les détecteurs MIMO existants, l'algorithme nommé détecteur à sphère (Sphere Decoder Algorithm: SDA) a vu le jour pour réduire la complexité de traitement par rapport à la technique de détection originale basée sur le maximum de vraisemblance (ML). En outre, il a été démontré que SDA atteint des performances optimales pour les systèmes non codés. Toutefois, pour les systèmes codés, d'autres simplifications dans l'algorithme de détection peuvent être utilisées sans altérer les performances en taux d'erreur. Dans ce contexte, le SDA peut être modifié afin de prévoir une détection basée sur des informations pondérées. LSD (List-Sphere Decoder) a été introduit comme une version à entrées/sorties pondérées de la version SDA originale. Ce travail de thèse traite les aspects algorithmique, architectural et de mise en oeuvre de la détection MIMO basée sur SDA et LSD. Le principal objectif est de proposer des solutions de mise en oeuvre de faible complexité, tout en considérant les exigences des systèmes de communication numérique en termes de débit, de flexibilité et de taux d'erreurs. En particulier, la première contribution est représentée par une amélioration de SDA, ce qui permet une augmentation significative du débit avec une complexité supplémentaire très limitée et sans dégradation en termes de performance en taux derreurs binaires. La méthode de détection proposée, appelée LASDA (Look-Ahead SDA), est basée sur des transformations formelles, à savoir Look-Ahead, recalage et pipeline et sur une stratégie modifiée de recherche arborescente. Une conception efficace de type VLSI du détecteur LASDA supportant un system MIMO 4x4 avec une modulation MAQ-16 est proposée. La deuxième contribution concerne une étude détaillée sur la flexibilité et la convergence de la détection itérative. Deux détecteurs à entrées/sorties pondérées (Soft-Input Soft-Output: SISO) sont considérés: LSD et un filtrage linéaire de faible complexité (Linear Minimum-Mean-Square-Error-Interference-Canceller (MMSE-IC)). Des diagrammes de transfert d'information mutuelle (EXIT charts) sont développés. Cette analyse est orientée pour obtenir les compromis possibles entre complexité et performance pour une implémentation matérielle flexible. La dernière contribution est liée à la conception d'un processeur à jeu d'instructions dédié à l'application (Application-Specific Instruction-set Processor (ASIP)) pour un détecteur SISO LSD. L'ASIP proposé supporte différentes configurations MIMO (2x2, 3x3, 4x4) et différents ordres de modulation (QPSK, MAQ-16, MAQ-64) en plus d'une taille de liste flexible (1 à 64 éléments)

Algorithms and architectures for the detection of MIMO signals

Les systèmes multi-antennes (Multiple-Input Multiple-Output: MIMO) représentent une technologie clé pour le déploiement de systèmes de communication sans fil. Cependant, la complexité des détecteurs MIMO de haut débit pose un problème sérieux de mise en oeuvre. Parmi les détecteurs MIMO existants, l algorithme nommé détecteur à sphère (Sphere Decoder Algorithm: SDA) a vu le jour pour réduire la complexité de traitement par rapport à la technique de détection originale basée sur le maximum de vraisemblance (ML). En outre, il a été démontré que SDA atteint des performances optimales pour les systèmes non codés. Toutefois, pour les systèmes codés, d autres simplifications dans l algorithme de détection peuvent être utilisées sans altérer les performances en taux d erreur. Dans ce contexte, le SDA peut être modifié afin de prévoir une détection basée sur des informations pondérées. LSD (List-Sphere Decoder) a été introduit comme une version à entrées/sorties pondérées de la version SDA originale. Ce travail de thèse traite les aspects algorithmique, architectural et de mise en oeuvre de la détection MIMO basée sur SDA et LSD. Le principal objectif est de proposer des solutions de mise en oeuvre de faible complexité, tout en considérant les exigences des systèmes de communication numérique en termes de débit, de flexibilité et de taux d erreurs. En particulier, la première contribution est représentée par une amélioration de SDA, ce qui permet une augmentation significative du débit avec une complexité supplémentaire très limitée et sans dégradation en termes de performance en taux derreurs binaires. La méthode de détection proposée, appelée LASDA (Look-Ahead SDA), est basée sur des transformations formelles, à savoir Look-Ahead, recalage et pipeline et sur une stratégie modifiée de recherche arborescente. Une conception efficace de type VLSI du détecteur LASDA supportant un system MIMO 4x4 avec une modulation MAQ-16 est proposée. La deuxième contribution concerne une étude détaillée sur la flexibilité et la convergence de la détection itérative. Deux détecteurs à entrées/sorties pondérées (Soft-Input Soft-Output: SISO) sont considérés: LSD et un filtrage linéaire de faible complexité (Linear Minimum-Mean-Square-Error-Interference-Canceller (MMSE-IC)). Des diagrammes de transfert d information mutuelle (EXIT charts) sont développés. Cette analyse est orientée pour obtenir les compromis possibles entre complexité et performance pour une implémentation matérielle flexible. La dernière contribution est liée à la conception d un processeur à jeu d instructions dédié à l application (Application-Specific Instruction-set Processor (ASIP)) pour un détecteur SISO LSD. L ASIP proposé supporte différentes configurations MIMO (2x2, 3x3, 4x4) et différents ordres de modulation (QPSK, MAQ-16, MAQ-64) en plus d une taille de liste flexible (1 à 64 éléments).Multiple Input Multiple Output (MIMO) systems are recognized as a key enabling technology in high performance wireless communications. However the complexity of high throughput MIMO detectors poses a serious implementation issue. Among known MIMO detectors, Sphere Decoder Algorithm (SDA) has emerged to reduce the processing complexity, with respect to the original Maximum Likelihood (ML) detection. Moreover, it has been demonstrated that the SDA achieves optimal performance for uncoded systems. However, for coded systems, further simplifications in the detection algorithm can be used without altering the error rate performance if iterative detection and channel decoding is adopted in the receiver. Such an iterative processing with a channel decoder offers significant improvement in error-rate performance for a reduced signal-to-noise ratio. In this context, the SDA can be further simplified and modified in order to provide soft detection: List Sphere Decoder (LSD) has been introduced as a soft version of the original SDA. This research thesis focuses on algorithmic, architectural and implementation aspects of the Sphere Decoder Algorithm and the List Sphere Decoder . The main objective of the conducted work is to propose area-efficient implementation solutions while considering throughput, flexibility, and error rate performance requirements of advanced digital communication systems. In particular, the first contribution is represented by an improved SDA, which enables significant throughput increase at a very limited additional complexity and with no degradation in terms of Bit Error Rate performance. The proposed detection method, called LASDA (Look Ahead SDA) is based on formal algorithm transformations, namely look ahead, retiming and pipelining, besides a modified tree search strategy. An efficient VLSI design of LASDA detector supporting a 4x4 MIMO channel with 16QAM modulation is proposed. Synthesis results for a 130 nm technology are detailed. The second contribution concerns a detailed study on flexibility and convergence of iterative detection and channel decoding. In this regard, two Soft-Input Soft-Output detectors are considered: List Sphere Decoding and a low complexity linear filtering (Linear Minimum-Mean-Square-Error-Interference-Canceller (MMSE-IC)). Extrinsic Information Transfer (EXIT) charts are developed. This analysis is oriented to obtain possible performance-complexity trade-offs for a flexible hardware implementation. The last contribution is related to the proposal and design of an Application-Specific-Instruction set-Processor (ASIP) for SISO List Sphere Decoding. The proposed ASIP supports different MIMO system configurations (2x2, 3x3, 4x4) and modulation orders (QPSK, 16QAM, 64QAM) besides a flexible list size (from 1 to 64 elements). Synthesis results for a 130 nm technology are detailed.CESSON SEVIGNE-Télécom Breta (350512301) / SudocSudocFranceF