Sunil Bisnath

Current State of Precise Point Positioning and Future Prospects and Limitations

The Precise Point Positioning Working Group within the Next Generation RTK Sub- Commission of IAG Commission 4 has been involved with Precise Point Positioning (PPP) developments for the past few years. The information presented here summarizes the Working Groups findings concern- ing the state of PPP technology, and discusses the probable near-term future potential and limitations of the technique. The broad question of the place of PPP within the future spectrum of space geodetic measurement techniques is addressed by investigating specific aspects of the method.

Uncovering common misconceptions in GNSS Precise Point Positioning and its future prospect

Within the last decade, GNSS Precise Point Positioning (PPP) has generated unprecedented interest among the GNSS community and is being used for a number of scientific and commercial applications today. Similar to the conventional relative positioning technique, PPP could provide positioning solutions at centimeter-level precision by making use of the precise carrier phase measurements and high-accuracy satellite orbits and clock corrections provided by, for example, the International GNSS Service. The PPP technique is attractive as it is computationally efficient; it eliminates the need for simultaneous observations at both the reference and rover receivers; it also eliminates the needs for the rover receiver to operate within the vicinity of the reference receiver; and it provides homogenous positioning quality within a consistent global frame anywhere in the world with a single GNSS receiver. Although PPP has definite advantages for many applications, its merits and widespread adoption are significantly limited by the long convergence time, which restricts the use of the PPP technique for many real-time GNSS applications. We provide an overview of the current performance of PPP as well as attempt to address some of the common misconceptions of this positioning technique—considered by many as the future of satellite positioning and navigation. Given the upcoming modernization and deployment of GNSS satellites over the next few years, it would be appropriate to address the potential impacts of these signals and constellations on the future prospect of PPP.

Software simulation of multiple Global Navigation Satellite System measurements

The research discussed in this paper addresses the question of how to simulate realistic observables from current and pending Global Navigation Satellite Systems (GNSSs) in a way that is independent of the characteristics of specific systems. The generated observables can be used to predict future multi-GNSS performance and aid in the development of enhanced processing algorithms. This paper introduces a software simulator package called Multi-GNSS Observables Simulator (MGOS), which has been developed to generate pseudorange and carrier-phase measurements for the GPS, GLONASS, Galileo and Compass constellations. The key component of MGOS is its error source library. It has been developed to simulate the most common GNSS errors (such as orbit, atmospheric, clock, and hardware errors) for all aforementioned GNSSs.

Feature article: Design and implementation of a low-cost SoC-based software GNSS receiver

A global navigation satellite system (GNSS) receiver processes signals transmitted from the satellites to determine user position, velocity, and time. Compared to conventional receivers, a software GNSS receiver offers better design flexibility and requires fewer dedicated hardware components [1]. An ideal software receiver typically processes all signals in a processor; however, this method is not efficient practically, because it becomes a computational burden for the processor. For this reason, frequent multiplications and operations are offloaded to hardware elements such as a field-programmable gate array (FPGA).

Sensor-Driven Calibration and Co-Registration of Airborne Multisensor LiDAR Data

Abstract. In large-area LiDAR mapping projects, surveyors might collect data at different times and with different sensors, creating loosely connected laser point clouds with varying point densities, accuracies, and overlaps. Current LiDAR calibration methodologies refine each point cloud and evaluate the accuracy of each point cloud individually. In the case when a surface model is required, an individual DEM tile is derived from each point cloud separately. This traditional workflow often causes geometric inconsistencies in the transitional zones of neighboring survey areas and introduces difficulties in the mosaicking process of the DEM tiles. In this article, a new methodology for generating geometrically correct laser point clouds—free of blunders and systematic errors—and seamless co-registration of multiple neighboring laser point clouds with minimal ground control input is introduced. Datasets collected at different times and/or with multiple equipment can be geometrically rectified in a fully automated fashion through improved sensor parameters, either simultaneously or sequentially within the same least squares adjustment, resulting in a steady flow of accuracy in the overlap zones. Further, by processing adjacent laser point clouds, it is further shown how this procedure reduces the geometric inconsistencies from, initially, several decimeters to a few centimeters and achieves an absolute accuracy of a few centimeters across all survey blocks, consistently, using just one control point. Building on this unique methodology, a new, simplified process for generating more homogenous and more accurate DEM products is suggested. Résumé. Pour des projets de cartographie LiDAR de grande envergure, les géomètres peuvent recueillir des données à des moments différents et avec des capteurs différents. Ceci produit des nuages de points laser aux liens assez lâches avec des densités de points, des précisions et des chevauchements différents. Les méthodologies actuelles de rectification LiDAR affinent et corrigent chaque nuage de points individuellement, ce qui provoque souvent des incohérences géométriques dans les zones de transition des carreaux de levés topographiques voisins et introduit des difficultés dans la création de mosaïques modèles numériques d’élévation (MNE)«Digital Elevation Model (DEM)». Dans cet article, est introduite une nouvelle méthode de rectification LiDAR, qui permet de joindre des nuages de points laser voisins sans discontinuités avec un minimum de point de référence au sol. Des ensembles de données collectées à des moments différents et/ou avec du matériel différent peuvent être corrigés simultanément ou successivement dans le même ajustement des moindres carrés, résultant en un flux continu de précision dans les zones de chevauchement. Il est en outre montré comment cette procédure réduit les incohérences géométriques et la perte d’information généralement associées avec le processus de création de mosaïques MNE «DEM» traditionnel, et réalise des produits MNE «DEM» plus homogènes, cohérents, et précis.