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Numerical Analysis of GNSS Signal Outage Effect on EOPs Solutions Using Tightly Coupled GNSS/IMU Integration: A Simulated Case Study in Sweden

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SENSORS 2023年第14期23卷 6361-6361页

作者： Jouybari, Arash Bagherbandi, Mohammad Nilfouroushan, Faramarz Univ Gavle Fac Engn & Sustainable Dev SE-80176 Gavle Sweden Royal Inst Technol KTH Div Surveying Geodesy Land Law & Real Estate Plann SE-10044 Stockholm Sweden Lantmateriet Dept Geodet Infrastruct Geodata Div SE-80182 Gavle Sweden

The absence of a reliable Global Navigation Satellite System (GNSS) signal leads to degraded position robustness in standalone receivers. To address this issue, integrating GNSS with inertial measurement units (IMUs) can improve positioning accuracy. This article analyzes the performance of tightly coupled GNSS/IMU integration, specifically the forward Kalman filter and smoothing algorithm, using both single and network GNSS stations and the post-processed kinematic (PPK) method. Additionally, the impact of simulated GNSS signal outage on exterior orientation parameters (EOPs) solutions is investigated. Results demonstrate that the smoothing algorithm enhances positioning uncertainty (RMSE) for north, east, and heading by approximately 17-43% (e.g., it improves north RMSE from 51 mm to a range of 42 mm, representing a 17% improvement). Orientation uncertainty is reduced by about 60% for roll, pitch, and heading. Moreover, the algorithm mitigates the effects of GNSS signal outage, improving position uncertainty by up to 95% and orientation uncertainty by up to 60% using the smoothing algorithm instead of the forward Kalman filter for signal outages up to 180 s.

关键词： GNSS INS integration forward Kalman filter smoothing algorithm tightly coupled PPK virtual reference station aerial photogrammetry

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Optimizations for the EcoPod field identification tool

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BMC BIOINFORMATICS 2008年第1期9卷 150-150页

作者： Manoharan, Aswath Stamberger, Jeannie Yu, YuanYuan Paepcke, Andreas Stanford Univ Dept Comp Sci Stanford CA 95305 USA Stanford Univ Dept Biol Stanford CA 95305 USA

Background: We sketch our species identification tool for palm sized computers that helps knowledgeable observers with census activities. An algorithm turns an identification matrix into a minimal length series of questions that guide the operator towards identification. Historic observation data from the census geographic area helps minimize question volume. We explore how much historic data is required to boost performance, and whether the use of history negatively impacts identification of rare species. We also explore how characteristics of the matrix interact with the algorithm, and how best to predict the probability of observing a previously unseen species. Results: Point counts of birds taken at Stanford University's Jasper Ridge Biological Preserve between 2000 and 2005 were used to examine the algorithm. A computer identified species by correctly answering, and counting the algorithm's questions. We also explored how the character density of the key matrix and the theoretical minimum number of questions for each bird in the matrix influenced the algorithm. Our investigation of the required probability smoothing determined whether Laplace smoothing of observation probabilities was sufficient, or whether the more complex Good-Turing technique is required. Conclusion: Historic data improved identification speed, but only impacted the top 25% most frequently observed birds. For rare birds the history based algorithms did not impose a noticeable penalty in the number of questions required for identification. For our dataset neither age of the historic data, nor the number of observation years impacted the algorithm. Density of characters for different taxa in the identification matrix did not impact the algorithms. Intrinsic differences in identifying different birds did affect the algorithm, but the differences affected the baseline method of not using historic data to exactly the same degree. We found that Laplace smoothing performed better for rare species t

关键词： Natural Language Processing smoothing algorithm Laplace smoothing Bird Observation Question Tree

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Uncertainty in the Back-Calculation of Geometric Parameters of Vertical Curves Obtained with UAV

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JOURNAL OF SURVEYING ENGINEERING 2023年第1期149卷 04022015-04022015页

作者： Ortiz-Morales, Gerardo Echaveguren, Tomas Cartes, Pablo Rivas-Medina, Alicia Univ Concepcion Fac Engn Dept Civil Engn Concepcion 4070409 Bio Bio Chile Tech Univ Madrid UPM Sch Surveying Geodesy & Cartog Dept Surveying & Cartog Engn Madrid 28031 Spain

In existing roads, the geometrical parameters of the alignment are the primary input for safety or geometrical improvement studies. However, the as-built drawings are not always available to obtain geometrical parameters, whereby they must be back-calculated from surveying data. The procedures to back-calculate geometrical parameters of existing roads and fit profile data use parametric methods such as polynomials or explicit functions and nonparametric methods such as splines or smoothers. In smoother-based methods, a usual computing decision is to consider a fixed spacing, one smoothing algorithm, and one set of smoothing parameters to obtain a single set of curvature, deflection, and length (KAL) parameters of vertical curves. Therefore, different values of KAL parameters will be obtained depending on the choice of spacing, smoothing algorithm, and smoothing parameters. This paper aims to study the relative effect in the variability of KAL parameters of a vertical curve, introduced by several spacing combinations, smoothers, and parameters, using data obtained with an unmanned aerial vehicle (UAV). Elevation and slope data were obtained from a digital elevation model every 2, 5, and 10 m. The slope-horizontal distance diagrams were smoothed using single, double, and triple exponential smoothing for different levels, trends, and season parameters. The KAL parameters were back-calculated for each slope-horizontal distance diagram, and the variability analysis was undertaken with boosting regression, multiple analysis of variance, and k-nearest neighbor algorithm and tested using receiver operating characteristics (ROC) curves. Results show that the smoothing algorithm and parameters choice affected mainly the K parameter and that the single exponential smoothing algorithm is more suitable than double and triple exponential smoothing algorithms to estimate the KAL parameters.

关键词： Vertical curve geometry Unmanned aerial vehicle (UAV) photogrammetry smoothing algorithm Slope-horizontal distance diagram

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A robust GNSS sensors in presence of signal blockage for USV application

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MEASUREMENT SCIENCE AND TECHNOLOGY 2024年第3期35卷 035124-035124页

作者： Liu, Wei Huang, Hua Hu, Yuan Han, Bing Wang, Shengzheng Shanghai Maritime Univ Merchant Marine Coll Shanghai 201306 Peoples R China Shanghai Ocean Univ 999 Hucheng Ring Rd Shanghai 201306 Peoples R China Shanghai Ship & Shipping Res Inst Shanghai 200135 Peoples R China

Unmanned surface vehicle (USV) can navigate autonomously via the global navigation satellite system (GNSS). However, the traditional GNSS scalar tracking loop easily loses lock in low carrier-to-noise ratio (CNR) situations, such as signal occlusion and weak signals. Meanwhile, an increase in the carrier/code phase error leads to an increase in the measurement error of the navigation filter, which decreases the accuracy of the position estimation. To solve this problem, this paper proposes a carrier and code tracking structure based on a forward and backward Kalman filter to dynamically adjust the gain of the vector tracking loop. The carrier and code phase errors calculated by the loop discriminators were linearly transformed into pseudo-range rate and pseudo-range errors after filtering and smoothing, which were used as the measurements of the navigation filter. The signal CNR was used to adaptively adjust the measurement noise covariance matrix of the loop filters. The field tests used a commercial receiver's navigation solution as the reference. In the stationary test, the proposed structure reduced the localization error by 44.3% compared with the traditional methods. In kinematic experiments, the proposed structure reduced the carrier and code phase errors in a harsh signal environment and improved the positioning accuracy at the source. The test results demonstrate that the proposed GNSS tracking method can provide a possible solution for the development of navigation systems for USV.

关键词： unmanned surface vehicle GNSS signal blockage vector tracking Kalman filter smoothing algorithm

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Kolmogorov-Zurbenko filters in spatiotemporal analysis

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WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL STATISTICS 2018年第1期10卷 e1419页

作者： Zurbenko, Igor G. Smith, Devin SUNY Albany Dept Epidemiol & Biostat Albany NY 12222 USA

This paper is an extension of WIRE publication Kolmogorov-Zurbenko filters, 2010. It addresses computational aspects of multidimensional KZ filtering for unevenly spaced data. Some real examples are provided to illustrate some of the details of such data analysis. The identification and separation of different spatial or temporal scales in spatiotemporal data can provide essential improvements to the accuracy of explanations. In particular, long term scales can be made to display clear patterns which are absolutely indistinguishable using standard multivariate analysis methods. (C) 2017 Wiley Periodicals, Inc.

关键词： KZ Filter KZFT moving average spectrum estimation smoothing algorithm spatial data time series time series data

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An algorithm for the Removal of Spurious Oscillations from Spectra Derived from THz Time-Domain Data

An Algorithm for the Removal of Spurious Oscillations from S...

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32nd International Conference on Infrared and Millimeter Waves, and 15th International Conference on Terahertz Electronics (IRMMW-THz 2007), part 1

作者： M. Naftaly R. E. Miles School of Electronic and Electrical Engineering University of Leeds UK

ISBN: (纸本)9781424414383

We present a simple algorithm for removing or reducing spurious oscillations in the THz spectra which result from secondary reflection peaks in samples or optical elements. The algorithm utilizes the fact that a THz time-domain trace containing secondary peaks can be represented as a convolution of the main peak and two or more delta functions.

关键词： THz time-domain spectroscopy Spurious oscillations Secondary reflections smoothing algorithm

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THE GAUSS-NEWTON algorithm APPLIED TO TRACK-WHILE-SCAN RADAR

THE GAUSS-NEWTON ALGORITHM APPLIED TO TRACK-WHILE-SCAN RADAR

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IET International Conference on Radar Systems (Radar 2007)

作者： N. Morrison R. T. Lord M. R. Inggs Radar Remote Sensing Group Department of Electrical Engineering University of Cape Town Cape Town South Africa

The Gauss-Newton (GN) algorithm is the minimum-variance non-recursive estimation procedure invented by Gauss in 1809 [3, 4, 7]. Mathematicians refer to it by that name;statisticians refer to it as nonlinear regression;astronomers call it differential correction. In 1959 Swerling reworked Gauss' non-recursive algorithm into a recursive format [9], giving rise to the Bayes-Swerling filter. In 1960/61, Kalman and Bucy published their algorithm [5, 6], which, in the absence of process noise, can be derived from Swerling's recursive format [7]. The huge advances in computing power and affordability of RAM since the early 60's have made it desirable that we re-examine Gauss' original algorithm which avoids the problems and/or limitations incurred by either the Swerling or the Kalman recursive formats, and at the same time opens up tremendous flexibility in terms of access to internal filter values. This paper examines the GN algorithm and how it has been applied to Track-While-Scan (TWS) radar. A companion paper in these proceedings discusses the application of GN to Passive Coherent Location (PCL) radar [8].

关键词： Gauss-Newton smoothing algorithm Radar Tracking Nonlinear Regression Differential Correction

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Study on Pretreatment algorithm of Near Infrared Spectroscopy

Study on Pretreatment Algorithm of Near Infrared Spectroscop...

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第四届国际计算机与计算技术在农业中的应用研讨会

作者： Xiaoli Wang Guomin Zhou Agricultural Information Institute of CAAS

Pretreatment of near-infrared spectral data is the basis of feature extraction,quantitative and qualitative analysis and establishment of models,it plays a significant role in obtaining the data and get reliable *** purpose of the paper is compared the advantages and disadvantages of the S-G,derivative and multiple algorithm methods of spectral preprocessing through the example of apple leaves.S-G algorithm can smooth the data relatively better,but we must according to the specific circumstances of the case while chose the width of the window and the order of polynomial;Kernel smoothing is better than S-G in two-ends data processing,but its processing speed is slower than *** algorithm can get more stable reflectance,but it is sensitive to noise,so it need to be used with the smoothing *** scatter correction can be used effectively to eliminate the translation and offset of *** of above algorithms have been applied in the system of near infrared spectroscopy processing system of leaves and satisfactory result was obtained.

关键词： Near Infrared Spectroscopy Spectral pretreatment smoothing algorithm Derivative algorithm Multiple scatter correction algorithms

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EGI/IMU Integration Using Multiple IMUs and Error Damping Loop for SAR Motion Compensation

EGI/IMU Integration Using Multiple IMUs and Error Damping Lo...

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International Conference on Control, Automation and Systems

作者： Jin Woo Song Chul Woo Kang Young Bum Park Yong Gon Jong Park Chan Gook Park BK21 Plus Transformative Training Program for Creative Mechanical and Aerospace Engineers Department of Mechanical and Aerospace Engineering Seoul National University Automations and Systems Research Institute Department of Mechanical and Aerospace Engineering Seoul National University Department of Mechanical and Aerospace Engineering/ASRI Seoul National University

ISBN: (纸本)9781479999767

We propose an EGI/IMU integrated smoothing algorithm based on extended Kalman filter (EKF) for synthetic aperture radar (SAR) motion compensation. Conventional navigation algorithms have discontinuities intrinsically which are caused by the measurement update done by the Kalman filter. The discontinuities are as harmful to the SAR image quality significantly as the relative position error. In order to eliminate discontinuities and to reduce relative position error, an additional inertial measurement unit (IMU) is used with master embedded GNSS inertial navigation system (EGI). The additional IMU contributes to smoother output and navigation accuracy. The error correction by EKF is performed gradually between measurement updates, which significantly improves the smoothing performance. Through Monte-Carlo simulation, the performance improvements in relative accuracy and continuity are confirmed.

关键词： smoothing algorithm SAR motion compensation EGI Extended Kalman filter

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