Huib de Ligt

Bio: Huib de Ligt is an academic researcher from The University of Nottingham Ningbo China. The author has contributed to research in topics: Global Positioning System & GNSS applications. The author has an hindex of 4, co-authored 13 publications receiving 60 citations. Previous affiliations of Huib de Ligt include Graz University of Technology & University of Nottingham.

1 Hz GPS satellites clock correction estimations to support high-rate dynamic PPP GPS applied on the Severn suspension bridge for deflection detection

Abstract: The use of GPS for deflection and vibration detection in structures requires a data rate of 1 Hz or higher. We investigate the advantages of utilizing high-rate satellite clocks in a dynamic PPP processing strategy specifically applied to the measurement of the deflections of bridges. A dataset consisting of 96 globally distributed stations was used for GPS satellite clocks estimates. The undifferenced float ambiguity (FAmb) and the Zenith Total Delay (ZTD) parameters were first estimated using PPP in static mode. The 1 Hz clock products of the GPS satellites were then successfully estimated by applying the FAmb and tropospheric delays as constraints to the carrier phase. The techniques are compared to 30-s and 300-s clock corrections obtained from the IGS, as well as double differenced solutions, through two experiments. The first experiment uses a rotating-arm apparatus, consisting of a portable rig located at the University of Nottingham Ningbo China, incorporating a 4 m long arm that rotates at a constant speed through the use of an electric motor. The 1-s GPS satellite clocks gave the most precise and stable PPP solution. The second experiment investigates the dynamic deflections of the Severn Bridge's suspension cables and towers, estimated using both the PPP, using our 1-s clock corrections as well as the IGS's 30-s and 300-s clock corrections, and the double differenced (DD) GPS data processing method. Correlation coefficient and standard deviation of the PPP solution and DD solution reflect the bridge's displacement waveform consistency and accuracy, respectively. Numerical analysis of the correlation coefficient and standard deviation of the time series, processed with different satellite clock intervals, implies that improvement can be achieved by applying the short interval satellites clock products that we propose. The strong agreement of the waveforms, calculated from the high-rate PPP, with the DD and the bridge load data, demonstrates that high-rate PPP is a viable alternative to the DD method for structural monitoring and an optimal option at times when DD is impossible due to the failure or inappropriateness of using a reference station.

Precipitable Water Vapour Retrieval from GPS Precise Point Positioning and NCEP CFSv2 Dataset during Typhoon Events.

Abstract: Radiosonde is extensively used for understanding meteorological parameters in the vertical direction. Four typhoon events, including three landfalls (MERANTI, NEPARTAK, and MEGI) and one non-landfall (MALAKAS), were chosen in analysing the precipitable water vapour (PWV) characteristics in this study. The spatial distribution of the three radiosonde stations in Zhejiang province does not meet the requirement in analysing changes in PWV during typhoon event. Global position system (GPS) observations are an alternative method for deriving the PWV. This enables improvements in the temporal⁻spatial resolution of PWV computed by the radiosonde measurements. The National Centers for Environmental Prediction (NCEP) re-analysed data were employed for interpolating temperature and atmosphere pressure at the GPS antennas height. The PWV computed from GPS observations and NCEP re-analysed data were then compared with the true PWV. The maximum difference of radiosonde and GPS PWV was not more than 30 mm at Taiz station. The Root-Mean-Square (RMS) of PWV differences between radiosonde and GPS was not more than 5 mm in January, February, March, November, and December. It was slightly greater than 5 mm in April. High RMS in May, June, July, August, September, and October implies that differences in GPS and radiosonde PWVs are evident in these months. Correlation coefficients of GPS and radiosonde PWVs were more than 0.9, indicating that the changes in GPS and radiosonde PWVs are similar. Radiosonde calculated PWVs were used for GPS PWV calibration for understanding the PWV changes during the period of a typhoon event. The results from three landfall typhoons show that the average PWV over Zhejiang province is increasing and approaching China mainland. In contrast, MALAKAS did not make landfall and shows a decreasing PWV trend, although it was heading to China mainland. Generally, the PWV change can be used to predict whether the typhoon will make landfall in these cases. PWV spatial distribution of MERANTI shows that PWV peaks change along the typhoon epicenter over Zhejiang province.

Deflection characterisation of rotary systems using ground-based radar

Abstract: In the last two decades, an increase in large rotary machines/systems has been witnessed. To ensure safe operation of these systems especially due to extreme stress caused by centrifugal forces as well as the wind or water loadings, regular structural health monitoring (SHM) of the unbalanced parameters, particularly at the blade tips is necessary. For this, the use of non-contact sensors provides the most appropriate approach; however, millimetric out-of-plane deflection monitoring using non-contact sensors at distances >1 m has not been comprehensively addressed for rotary systems, like wind turbines. This study presents a modelling environment to simulate radar returns to analyse rotary systems. Employing Sammon mapping as a dimensionality reduction procedure in conjunction with 2D visualisation, the study demonstrates the characterisation of dynamic deflection parameters using a fast, portable ground-based interferometric radar (GBR). Comparisons between the GBR results with those of a Leica AR20 GPS indicate a divergence ±12.79 mm. The study utilises SHM framework to acquire, normalise, extract, and validate GBR signals within an SHM framework for structures under test or for deflection validation of the new system. Further, it contributes to the non-contact structural fatigue damage detection during design, testing, and operating stages of rotary structures blade tips.

'The Micro-Doppler Effect in Radar' by V.C. Chen

Abstract: This is a book review of 'The Micro-Doppler Effect in Radar' by V. C. Chen. Artech House, 16 Sussex Street, London, SW1V 4RW, UK. 2011. 290pp + diskette. Illustrated. £90. ISBN 978-1-60807-057-2.

The Global Positioning System

Abstract: This research study explores the Global Positioning System (GPS), its history, and the process of discovery needed to create the most accurate GPS possible, as well as the contemporary applications of GPS technology. Starting with the first satellite in space, GPS has been a work in progress. Originally pursued by the military for improvements to military tactics, GPS has become integrated into the everyday lives of millions of people around the world. How GPS determines location is a dichotomy, with simplistic theory and complex application. Many factors go into GPS to provide a consistent, accurate location. The orbital planes the satellites are placed in provide 24/7 coverage globally, the L-band frequencies used were chosen specifically for the characteristics they possess, and the multiple atomic clocks installed on each satellite provide incredible accuracy down to the nanoseconds, which is quintessential in GPS accuracy. The applications in GPS are far reaching and more applications are continually being discovered. With as far as GPS technology has progressed, there are still several factors that degrade the signal and are a challenge to overcome. Many of these challenges can be corrected efficiently, however, others, such as scintillation and total electron content variability in the ionosphere, create major hurdles to overcome. Luckily, there are many programs that aid in the correction process of these hurdles. The History of GPS According to R. Saunders’ article ​A Short History of GPS Development,​ The Global Positioning System (GPS) has a long history of trial and error and refinement and improvement. It’s purpose has shifted from being a military strategic asset to commonplace among the general public with its use in traveling, farming, and even banking. The beginning of GPS, introduced with a simple idea, can be traced back to the Soviet Union in the late 1950’s. In 1957, the Soviet Union made history with successfully launching the first satellite in space. To track the satellite Sputnik, Physicists and Scientists at John Hopkins University’s Applied Physics Laboratory listened to the beeps Sputnik’s signals produced. They noticed that the beeps had a Doppler Effect or Doppler Shift as the satellite passed by. Much like the sound a siren makes as a fire truck approaches, then as it passes, the sound of the siren seems different. The change in timing between the beeps let the scientist know Sputnik’s location. This led to the idea of reversing that process, to give a location on the Earth. Using radio frequencies to determine location in a two dimensional plane had been around since WWII, but using satellites would push this technology into the three dimensional realm. The United States Navy, Army, and Air Force all began developing their own GPS satellites in the 1960’s, but this was no small task. In the early 1960’s, the Navy launched its first Transit Satellite. The failure of this satellite, however, was due to

Human Activity Classification With Radar: Optimization and Noise Robustness With Iterative Convolutional Neural Networks Followed With Random Forests

Abstract: The accurate classification of activity patterns based on radar signatures is still an open problem and is a key to detect anomalous behavior for security and health applications. This paper presents a novel iterative convolutional neural network strategy with an autocorrelation pre-processing instead of the traditional micro-Doppler image pre-processing to classify activities or subjects accurately. The proposed strategy uses an iterative deep learning framework for the automatic definition and extraction of features. This is followed by a traditional supervised learning classifier to label different activities. Using three human subjects and their real motion captured data, 12 000 radar signatures were simulated by varying additive white Gaussian noise. In addition, 6720 experimental radar signatures were captured with a frequency-modulated continuous radar at 5.8 GHz with 400 MHz of instantaneous bandwidth from seven activities using one subject and 4800 signatures from five subjects while walking. The simulated and experimental data were both used to validate our proposed method, with signal–noise ratio varying from −20 to 20 dB and with 88.74% average accuracy at −10 dB and 100% peak accuracy at 15 dB. The proposed iterative convolutional neural networks followed with random forests not only outperform the feature-based methods using micro-Doppler images but also outperform the classification methods using other types of supervised classifiers after our proposed iterative convolutional neural network.