scholarly journals Seeking Optimal GNSS Radio Occultation Constellations Using Evolutionary Algorithms

2019 ◽  
Vol 11 (5) ◽  
pp. 571 ◽  
Author(s):  
Xiaohua Xu ◽  
Yi Han ◽  
Jia Luo ◽  
Jens Wickert ◽  
Milad Asgarimehr
Keyword(s):  
Evolutionary Algorithms ◽  
Radio Occultation ◽  
Weather Forecasting ◽  
Fitness Function ◽  
Sampling Rate ◽  
Pso Algorithm ◽  
Low Earth Orbit ◽  
Temporal Sampling ◽  
Leo Satellites ◽  
Lattice Flower Constellation

Given the great achievements of the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) mission in providing huge amount of GPS radio occultation (RO) data for weather forecasting, climate research, and ionosphere monitoring, further Global Navigation Satellite System (GNSS) RO missions are being followingly planned. Higher spatial and also temporal sampling rates of RO observations, achievable with higher number of GNSS/receiver satellites or optimization of the Low Earth Orbit (LEO) constellation, are being studied by high number of researches. The objective of this study is to design GNSS RO missions which provide multi-GNSS RO events (ROEs) with the optimal performance over the globe. The navigation signals from GPS, GLONASS, BDS, Galileo, and QZSS are exploited and two constellation patterns, the 2D-lattice flower constellation (2D-LFC) and the 3D-lattice flower constellation (3D-LFC), are used to develop the LEO constellations. To be more specific, two evolutionary algorithms, including the genetic algorithm (GA) and the particle swarm optimization (PSO) algorithm, are used for searching the optimal constellation parameters. The fitness function of the evolutionary algorithms takes into account the spatio-temporal sampling rate. The optimal RO constellations are obtained for which consisting of 6–12 LEO satellites. The optimality of the LEO constellations is evaluated in terms of the number of global ROEs observed during 24 h and the coefficient value of variation (COV) representing the uniformity of the point-to-point distributions of ROEs. It is found that for a certain number of LEO satellites, the PSO algorithm generally performs better than the GA, and the optimal 2D-LFC generally outperforms the optimal 3D-LFC with respect to the uniformity of the spatial and temporal distributions of ROEs.

scholarly journals Simultaneous Radio Occultation Predictions for Inter-Satellite Comparison of Bending Angle Profiles from COSMIC-2 and GeoOptics

2021 ◽  
Vol 13 (18) ◽  
pp. 3644
Author(s):  
Yong Chen ◽  
Xi Shao ◽  
Changyong Cao ◽  
Shu-peng Ho
Keyword(s):  
Radio Occultation ◽  
International System ◽  
Weather Prediction ◽  
Prediction Method ◽  
Low Earth Orbit ◽  
Weather Data ◽  
Bending Angle ◽  
System Of Units ◽  
Leo Satellites ◽  
Bending Angles

The Global Navigation Satellite System (GNSS) radio occultation (RO) is a remote sensing technique that uses International System of Units (SI) traceable GNSS signals for atmospheric limb soundings. The RO bending angle/sounding profiles are needed for assimilation in Numerical Weather Prediction (NWP) models, weather, climate, and space weather applications. Evaluating these RO data to ensure the high data quality for these applications is becoming more and more critical. This study presents a method for predicting radio occultation events, from which simultaneous radio occultation (SRO) for a pair of low-Earth-orbit (LEO) satellites on the limb to the same GNSS satellite can be obtained. The SRO method complements the Simultaneous Nadir Overpass (SNO) method (for nadir viewing satellite instruments), which has been widely used to inter-calibrate LEO to LEO and LEO to geosynchronous-equatorial-orbit (GEO) satellites. Unlike the SNO method, the SRO method involves three satellites: a GNSS and two LEO satellites with RO receivers. The SRO method allows for the direct comparison of bending angles when the simultaneous RO measurements for two LEO satellites receiving the same GNSS signal pass through approximately the same atmosphere within minutes in time and within less than 200 km of distance from each other. The prediction method can also be applied to radiosonde overpass prediction, and coordinate radiosonde launches for inter-comparisons between RO and radiosonde profiles. The main advantage of the SRO comparisons of bending angles is the significantly reduced uncertainties due to the much shorter time and smaller atmospheric path differences than traditional RO comparisons. To demonstrate the usefulness of this method, we present a comparison of the Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2) and GeoOpitcs RO profiles using SRO data for two time periods: Commercial Weather Data (CWD) data delivery order-1 (DO-1): 15 December 2020–15 January 2021 and CWD DO-2: 17 March 2021–31 August 2021. The results show good agreement in the bending angles between the COSMIC-2 RO measurements and those from GeoOptics, although systematic biases are also found in the inter-comparisons. Instrument and processing algorithm performances for the signal-to-noise ratio (SNR), penetration height, and bending angle retrieval uncertainty are also characterized. Given the efficiency of this method and the many RO measurements that are publicly and commercially available as well as the expansion of receiver capabilities to all GNSS systems, it is expected that this method can be used to validate/inter-calibrate GNSS RO measurements from different missions.

scholarly journals GNSS RTK Positioning Augmented with Large LEO Constellation

2019 ◽  
Vol 11 (3) ◽  
pp. 228 ◽  
Author(s):  
Xingxing Li ◽  
Hongbo Lv ◽  
Fujian Ma ◽  
Xin Li ◽  
Jinghui Liu ◽  
...  
Keyword(s):  
Low Earth Orbit ◽  
Global Navigation Satellite Systems ◽  
Convergence Time ◽  
Current Status ◽  
Initial Assessment ◽  
Satellite Systems ◽  
Long Baseline ◽  
Leo Satellites ◽  
Global Navigation Satellite ◽  
Long Baselines

It is widely known that in real-time kinematic (RTK) solution, the convergence and ambiguity-fixed speeds are critical requirements to achieve centimeter-level positioning, especially in medium-to-long baselines. Recently, the current status of the global navigation satellite systems (GNSS) can be improved by employing low earth orbit (LEO) satellites. In this study, an initial assessment is applied for LEO constellations augmented GNSS RTK positioning, where four designed LEO constellations with different satellite numbers, as well as the nominal GPS constellation, are simulated and adopted for analysis. In terms of aforementioned constellations solutions, the statistical results of a 68.7-km baseline show that when introducing 60, 96, 192, and 288 polar-orbiting LEO constellations, the RTK convergence time can be shortened from 4.94 to 2.73, 1.47, 0.92, and 0.73 min, respectively. In addition, the average time to first fix (TTFF) can be decreased from 7.28 to 3.33, 2.38, 1.22, and 0.87 min, respectively. Meanwhile, further improvements could be satisfied in several elements such as corresponding fixing ratio, number of visible satellites, position dilution of precision (PDOP) and baseline solution precision. Furthermore, the performance of the combined GPS/LEO RTK is evaluated over various-length baselines, based on convergence time and TTFF. The research findings show that the medium-to-long baseline schemes confirm that LEO satellites do helpfully obtain faster convergence and fixing, especially in the case of long baselines, using large LEO constellations, subsequently, the average TTFF for long baselines has a substantial shortened about 90%, in other words from 12 to 2 min approximately by combining with the larger LEO constellation of 192 or 288 satellites. It is interesting to denote that similar improvements can be observed from the convergence time.

scholarly journals Cerebral CT Perfusion in Acute Stroke: The Effect of Lowering the Tube Load and Sampling Rate on the Reproducibility of Parametric Maps

Diagnostics ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1121
Author(s):  
Georgios S. Ioannidis ◽  
Søren Christensen ◽  
Katerina Nikiforaki ◽  
Eleftherios Trivizakis ◽  
Kostas Perisinakis ◽  
...  
Keyword(s):  
Cerebral Blood Volume ◽  
Ct Perfusion ◽  
Sampling Rate ◽  
Volumetric Analysis ◽  
Sampling Interval ◽  
Diagnostic Efficiency ◽  
Temporal Sampling ◽  
Sampling Intervals ◽  
The Mean ◽  
Parametric Maps

The aim of this study was to define lower dose parameters (tube load and temporal sampling) for CT perfusion that still preserve the diagnostic efficiency of the derived parametric maps. Ninety stroke CT examinations from four clinical sites with 1 s temporal sampling and a range of tube loads (mAs) (100–180) were studied. Realistic CT noise was retrospectively added to simulate a CT perfusion protocol, with a maximum reduction of 40% tube load (mAs) combined with increased sampling intervals (up to 3 s). Perfusion maps from the original and simulated protocols were compared by: (a) similarity using a voxel-wise Pearson’s correlation coefficient r with in-house software; (b) volumetric analysis of the infarcted and hypoperfused volumes using commercial software. Pearson’s r values varied for the different perfusion metrics from 0.1 to 0.85. The mean slope of increase and cerebral blood volume present the highest r values, remaining consistently above 0.7 for all protocol versions with 2 s sampling interval. Reduction of the sampling rate from 2 s to 1 s had only modest impacts on a TMAX volume of 0.4 mL (IQR −1–3) (p = 0.04) and core volume of −1.1 mL (IQR −4–0) (p < 0.001), indicating dose savings of 50%, with no practical loss of diagnostic accuracy. The lowest possible dose protocol was 2 s temporal sampling and a tube load of 100 mAs.

Missile Guidance Algorithm Design Using Particle Swarm Optimization

2013 ◽  
Vol 284-287 ◽  
pp. 2411-2415
Author(s):  
Chien Chun Kung ◽  
Kuei Yi Chen
Keyword(s):  
Objective Function ◽  
Fitness Function ◽  
Equations Of Motion ◽  
Algorithm Design ◽  
Solution Space ◽  
Pso Algorithm ◽  
Local Optimum ◽  
Missile Guidance ◽  
Pursuit Evasion ◽  
Guidance Algorithm

This paper presents a technique to design a PSO guidance algorithm for the nonlinear and dynamic pursuit-evasion optimization problem. In the PSO guidance algorithm, the particle positions of the swarm are initialized randomly within the guidance command solution space. With the particle positions to be guidance commands, we predict and record missiles’ behavior by solving point-mass equations of motion during a defined short-range period. Taking relative distance to be the objective function, the fitness function is then evaluated according to the objective function. As the PSO algorithm proceeds, these guidance commands will migrate to a local optimum until the global optimum is reached. This paper implements the PSO guidance algorithm in two pursuit-evasion scenarios and the simulation results show that the proposed design technique is able to generate a missile guidance law which has satisfied performance in execution time, terminal miss distance, time of interception and robust pursuit capability.

scholarly journals Topside Ionosphere and Plasmasphere Modelling Using GNSS Radio Occultation and POD Data

2021 ◽  
Vol 13 (8) ◽  
pp. 1559
Author(s):  
Fabricio S. Prol ◽  
M. Mainul Hoque
Keyword(s):  
Solar Activity ◽  
Electron Density ◽  
Radio Occultation ◽  
Geomagnetic Latitude ◽  
Low Earth Orbit ◽  
Activity Level ◽  
Topside Ionosphere ◽  
Electron Content ◽  
Total Electron ◽  
Solar Activity Level

A 3D-model approach has been developed to describe the electron density of the topside ionosphere and plasmasphere based on Global Navigation Satellite System (GNSS) measurements onboard low Earth orbit satellites. Electron density profiles derived from ionospheric Radio Occultation (RO) data are extrapolated to the upper ionosphere and plasmasphere based on a linear Vary-Chap function and Total Electron Content (TEC) measurements. A final update is then obtained by applying tomographic algorithms to the slant TEC measurements. Since the background specification is created with RO data, the proposed approach does not require using any external ionospheric/plasmaspheric model to adapt to the most recent data distributions. We assessed the model accuracy in 2013 and 2018 using independent TEC data, in situ electron density measurements, and ionosondes. A systematic better specification was obtained in comparison to NeQuick, with improvements around 15% in terms of electron density at 800 km, 26% at the top-most region (above 10,000 km) and 26% to 55% in terms of TEC, depending on the solar activity level. Our investigation shows that the developed model follows a known variation of electron density with respect to geographic/geomagnetic latitude, altitude, solar activity level, season, and local time, revealing the approach as a practical and useful tool for describing topside ionosphere and plasmasphere using satellite-based GNSS data.

scholarly journals Opportunistic In-Flight INS Alignment Using LEO Satellites and a Rotatory IMU Platform

Aerospace ◽  
2021 ◽  
Vol 8 (10) ◽  
pp. 280
Author(s):  
Farzan Farhangian ◽  
Hamza Benzerrouk ◽  
Rene Landry
Keyword(s):  
Kalman Filter ◽  
State Space Model ◽  
Flight Test ◽  
Satellite System ◽  
Low Earth Orbit ◽  
Measurement Unit ◽  
Starting Point ◽  
Leo Satellites ◽  
Positioning Method ◽  
Global Navigation Satellite

With the emergence of numerous low Earth orbit (LEO) satellite constellations such as Iridium-Next, Globalstar, Orbcomm, Starlink, and OneWeb, the idea of considering their downlink signals as a source of pseudorange and pseudorange rate measurements has become incredibly attractive to the community. LEO satellites could be a reliable alternative for environments or situations in which the global navigation satellite system (GNSS) is blocked or inaccessible. In this article, we present a novel in-flight alignment method for a strapdown inertial navigation system (SINS) using Doppler shift measurements obtained from single or multi-constellation LEO satellites and a rotation technique applied on the inertial measurement unit (IMU). Firstly, a regular Doppler positioning algorithm based on the extended Kalman filter (EKF) calculates states of the receiver. This system is considered as a slave block. In parallel, a master INS estimates the position, velocity, and attitude of the system. Secondly, the linearized state space model of the INS errors is formulated. The alignment model accounts for obtaining the errors of the INS by a Kalman filter. The measurements of this system are the difference in the outputs from the master and slave systems. Thirdly, as the observability rank of the system is not sufficient for estimating all the parameters, a discrete dual-axis IMU rotation sequence was simulated. By increasing the observability rank of the system, all the states were estimated. Two experiments were performed with different overhead satellites and numbers of constellations: one for a ground vehicle and another for a small flight vehicle. Finally, the results showed a significant improvement compared to stand-alone INS and the regular Doppler positioning method. The error of the ground test reached around 26 m. This error for the flight test was demonstrated in different time intervals from the starting point of the trajectory. The proposed method showed a 180% accuracy improvement compared to the Doppler positioning method for up to 4.5 min after blocking the GNSS.

Sign in / Sign up

Export Citation Format

Share Document