Millimeter-level Precision Research Articles

A Novel Algorithm for Precise Orbit Determination Using a Single Satellite Laser Ranging System Within a Single Arc for Space Surveillance and Tracking

A satellite laser ranging (SLR) system uses lasers to measure the range from ground stations to space objects with millimeter-level precision. Recent advances in SLR systems have increased their use in space surveillance and tracking (SST). The problem we are addressing, the precise orbit determination (POD) using one-dimensional range observations within a single arc, is challenging owing to infinite solutions because of limited observability. Therefore, general orbit determination algorithms struggle to achieve reasonable accuracy. The proposed algorithm redefines the cost value for orbit determination by leveraging residual tendencies in the POD process. The tendencies of residuals are quantified as R-squared values using Fourier series fitting to determine velocity vector information. The algorithm corrects velocity vector errors through the grid search method and least squares (LS) with a priori information. This approach corrects all six dimensions of the state vectors, comprising position and velocity vectors, utilizing only one dimension of the range observations. Simulations of three satellites using real data validate the algorithm. In all cases, the errors of the two-line element data (three-dimensional position error of 1 km and velocity error of 1 m/s, approximately) used as the initial values were reduced by tens of meters and the cm/s level, respectively. The algorithm outperformed the general POD algorithm using only the LS method, which does not effectively reduce errors. This study offers a more efficient and accurate orbit determination method, which improves the safety, cost efficiency, and effectiveness of space operations.

Visual guidance technology of flying cars based on multilevel markers and depth

Split-type flying car will play an important role in the future transportation. This paper adopts a guidance method that couples visual information and depth information, and improves the docking accuracy through the mutual cooperation of the drone and the vehicle. Firstly, a multilevel docking marker is designed to achieve adaptive target matching within different distances during the docking process. The marker has strong robustness and can adapt to complex scenes such as occlusion, strong light, and large angle tilting, providing the redundant corner points required for machine vision detection pose information accurately. Secondly, a three-dimensional pose estimation algorithm is proposed, which can introduce depth information to correct the homography matrix. The algorithm combines the advantages of strong robustness to multilevel marker detection and high accuracy of depth information, and can output millimeter-level precision pose information in different environments, different inclination angles, and different occlusions. Finally, a flying car model experiment was carried out, and the results showed that the guidance technology can obtain millimeter-level precise pose information during the entire process of long distance-near distance-completion of docking, thus realizing precise docking.

Micropatterning MXene/TiO2 Nanocomposite Ink for Gas Sensing

This work describes the preparation, characterization, and micropatterning of MXene(Ti3C2)/TiO2 nanocomposite inks. MXene nanopowder was oxidized to form MXene/TiO2 nanocomposite powder using an air-aging method. The MXene/TiO2 inks were prepared using deionized water (H2O) as the solvent/dispersant and polyvinylpyrrolidone (PVP) as the surfactant. Various techniques were utilized to characterize the MXene/TiO2 nanocomposite material, and the BET results showed the preferential adsorption of butane of the MXene/TiO2 coating. Utilizing an ultrasonic dispersion printer in conjunction with a stencil mask, the MXene/TiO2 nanocomposite ink was successfully printed onto a 10mm*10mm gold-plated silicon substrate. This process achieved millimeter-level precision control, enabling the printing of fine lines with a width of 1μm and a spacing of 0.05mm. Furthermore, this technique demonstrated the ability to render various complex patterns, thus exemplifying the potential of MXene/TiO2 nanocomposite ink in the field of micro- and nano-manufacturing.

Absolute Ranging with Time Delay Interferometry for Space-Borne Gravitational Wave Detection.

In future space-borne gravitational wave (GW) detectors, time delay interferometry (TDI) will be utilized to reduce the overwhelming noise, including the laser frequency noise and the clock noise etc., by time shifting and recombining the data streams in post-processing. The successful operation of TDI relies on absolute inter-satellite ranging with meter-level precision. In this work, we numerically and experimentally demonstrate a strategy for inter-satellite distance measurement. The distances can be coarsely determined using the technique of arm-locking ranging with a large non-ambiguity range, and subsequently TDI can be used for precise distance measurement (TDI ranging) by finding the minimum value of the power of the residual noises. The measurement principle is introduced. We carry out the numerical simulations, and the results show millimeter-level precision. Further, we perform the experimental verifications based on the fiber link, and the distances can be measured with better than 0.05 m uncertainty, which can well satisfy the requirement of time delay interferometry.

A High-Precision Baseline Calibration Method Based on Estimation of Azimuth Fringe Frequency with THz Interferometry SAR

In this study, repeat-pass synthetic aperture radar interferometry (repeat-pass THz InSAR) is first extended to the terahertz band, and it has tremendous potential in the application of high-resolution three-dimensional (3D) imaging due to its shorter wavelength, larger bandwidth, and greater sensitivity to elevation variation. The super-resolution and high sensitivity of THz InSAR pose greater demands on the baseline calibration for high-precision digital elevation model (DEM) generation. To meet the elevation accuracy requirement of THz InSAR, we propose a baseline calibration method relying on the estimation of the azimuth fringe frequency (EAFF) of the interferometric phase. Initially, a model for non-parallel sampling path errors within the squint SAR repeat-pass interferometry was established, and then, we conducted the theoretical analysis of the phase errors induced by the non-parallel errors. Following this, using a reference DEM, the relationship between the fringe frequency of the error phase and the bias in the repeat-path positioning was established. This allowed the estimation of the position errors to be transformed into the frequency spectrum estimation based on the FFT, which would mitigate the impact of unknown SAR sampling positions. Ultimately, we investigated the accuracy of the proposed EAFF calibration method, and the simulation showed that it can achieve the theoretical accuracy when the correlation coefficient exceeds 0.3. Furthermore, we configured the repeat-pass THz InSAR system with the 0.3 THz stepped-frequency radar. Compared to the conventional calibration based on ground control points (GCPs), the 3D reconstruction of both a knife and a terrain model, calibrated using the proposed EAFF algorithm, demonstrated that the elevation accuracy can achieve millimeter-level precision across the entire image swath. The above results also proved the great potential of THz InSAR in high-precision 3D imaging and remote sensing.

Dynamic displacement monitoring by integrating high-rate GNSS and accelerometer: on the possibility of downsampling GNSS data at reference stations

We combine accelerometer and asynchronous high-rate GNSS data to retrieve dynamic displacements. The method adopts relative GNSS positioning with observations of different sampling rates at rover and reference stations. The objective is to examine the feasibility of downsampling GNSS data at reference stations and thus, verify whether permanent GNSS networks collecting low-rate observations can serve as reference sites. The performance is assessed using a shake table to induce displacement waveforms. We show that the combined GNSS and accelerometer solution improves displacement accuracy by half compared to the GNSS-only one. Further accuracy improvement is obtained by applying the Rauch Tung Striebel (RTS) smoother. Consequently, it is reasonable to downsample high-rate GNSS data at the reference station even to a 2 s interval and preserve the displacement error below 1 mm. The results also reveal that a fusion of GNSS with accelerometer and RTS smoothing helps to mitigate the ephemeris error. With the assessment in the time–frequency domain, we show that the combined solution better recovers displacement waveforms than GNSS-only. For the former solution, the detected peak frequencies agree very well with those of the Linear Variable Differential Transformer responsible for providing the ground truth displacements, and the amplitude error does not exceed 0.5 mm. We conclude that the proposed approach based on asynchronous GNSS observations provides millimeter-level precision results and is better for reconciling dynamic displacements than a GNSS-only solution or simply integrating accelerometer data.

Wireless Binocular Stereovision Measurement System Based on Improved Coarse-to-Fine Matching Algorithm

To cope with the challenges some commonly used displacement sensors may face in structural health monitoring, we proposed a wireless binocular stereovision measurement system based on the improved coarse-to-fine matching algorithm. The vision measurement system can perceive multipoint three-dimensional displacement and consists of two cameras, one remote control unit, and a solar panel. The improved coarse-to-fine matching algorithm only requires a flat surface with some painted textures instead of designed markers with refined patterns (circle, square, and chessboard). Omitting the textures keeps a balance between measurement accuracy and the burden of the target installation in the actual field of structural health monitoring. The proposed coarse-to-fine matching algorithm utilizes scale-invariant feature transform (SIFT) points to generate a robust initial guess and combines improved least squares matching (LSM) algorithm for advanced corresponding point matching. A precalculated look-up table for interpolation and parallel computation is used for higher matching precision and computational efficiency. Several experiments were conducted to present the accuracy and feasibility of the proposed metering system. A simulation test, an indoor shaking table test with several commonly used displacement sensors, and an outdoor experiment consider the natural condition. Experimental results verified that the proposed matching methodology could achieve 0.2-pixel matching accuracy, 0.1 mm measuring precision in a laboratory, and millimeter-level precision in real conditions.

RELIABILITY OF THE GPS CARRIER-PHASE FIX SOLUTION UNDER HARSH CONDITION

Abstract. Once the unknown integer ambiguity values are resolved, the GPS carrier phase observation will be transformed into a millimeter-level precision measurement. However, GPS observation are prone to a variety of errors, making it a biased measurement. There are two components in identifying integer ambiguities: estimation and validation. The estimation procedure aims to determine the ambiguity's integer values, and the validation step checks whether the estimated integer value is acceptable. Even though the theory and procedures for ambiguity estimates are well known, the topic of ambiguity validation is still being researched. The dependability of computed coordinates will be reduced if a false fixed solution emerges from an incorrectly estimated ambiguity integer value. In this study, the reliability of the fixed solution obtained by using several base stations in GPS positioning was investigated, and the coordinates received from these bases were compared. In a conclusion, quality control measures such as employing several base stations will improve the carrier phase measurement's accuracy.

Incorporating Persistent Scatterer Interferometry and Radon Anomaly to Understand the Anar Fault Mechanism and Observing New Evidence of Intensified Activity

Interferometric Synthetic Aperture Radar (InSAR) monitors surface change and displacement over a large area with millimeter-level precision and meter-level resolution. Anar fault, with a length of ~200 km, is located in central Iran. Recent seismological studies on the fault indicated that it is approaching the end of its seismic cycle. Although a large earthquake is imminent, the mechanism of the fault is not well understood. Therefore, understanding and discovering the mechanism of Anar fault remains a challenge. Here, we present an approach of displacement fault analysis utilizing a combination of InSAR data obtained from the persistent scatterer interferometry (PSI) method and 178 Sentinel-1 images (ascending and descending) (2017–2020). We incorporated groundwater samples from 40 wells, radon concentration anomaly mapping, Global Positioning System (GPS), and 3D displacement measurement acquired over four years (2016–2020). We investigated and monitored the deformation of the fault plate’s behavior over the last three years (2017–2020) to explore new evidence and signature of displacement. The results show that the time series analysis in the fault range has an increasing displacement rate in all dimensions. We observed that the line-of-sight (LOS) displacement rate varied from −15 mm to 5 mm per year. Our calculations show that the E–W, N–S, and vertical displacement rates of the fault blocks are 2 mm to −2 mm, 6 mm to −6 mm, and 2 mm to −4 mm per year, respectively. An anomaly map of the radon concentration shows that the complete alignment of the high concentration ranges with the fault strike and the radon concentration increased on average from 23.85 Bq/L to 25.30 Bq/L over these three years. Therefore, we predict rising the radon concentration is due to the increase in activity which resulted in a deformation. Finally, our findings show that the Anar fault is an oblique and right-lateral strike-slip with a normal component mechanism. We validated the proposed method and our results by comparing the GPS field data and PSI measurements. The root mean square error (RMSE) of the PSI measurement is estimated to be 0.142 mm. Based on the supporting evidence and signature, we conclude that the Anar fault activity increased between 2017 and 2020.

HPIPS: A High-Precision Indoor Pedestrian Positioning System Fusing WiFi-RTT, MEMS, and Map Information.

In order to solve the problem of pedestrian positioning in the indoor environment, this paper proposes a high-precision indoor pedestrian positioning system (HPIPS) based on smart phones. First of all, in view of the non-line-of-sight and multipath problems faced by the radio-signal-based indoor positioning technology, a method of using deep convolutional neural networks to learn the nonlinear mapping relationship between indoor spatial position and Wi-Fi RTT (round-trip time) ranging information is proposed. When constructing the training dataset, a fingerprint grayscale image construction method combined with specific AP (Access Point) positions was designed, and the representative physical space features were extracted by multi-layer convolution for pedestrian position prediction. The proposed positioning model has higher positioning accuracy than traditional fingerprint-matching positioning algorithms. Then, aiming at the problem of large fluctuations and poor continuity of fingerprint positioning results, a particle filter algorithm with an adaptive update of state parameters is proposed. The algorithm effectively integrates microelectromechanical systems (MEMS) sensor information in the smart phone and the structured spatial environment information, improves the freedom and positioning accuracy of pedestrian positioning, and achieves sub-meter-level stable absolute pedestrian positioning. Finally, in a test environment of about 800 m2, through a large number of experiments, compared with the millimeter-level precision optical dynamic calibration system, 94.2% of the positioning error is better than 1 m, and the average positioning error is 0.41 m. The results show that the system can provide high-precision and high-reliability location services and has great application and promotion value.

THE USE OF TERRESTRIAL LASER SCANNING TECHNIQUES TO EVALUATE INDUSTRIAL MASONRY CHIMNEY VERTICALITY

Abstract. This paper presents a strategy to measure verticality deviations (i.e. inclination) of tall chimneys. The method uses laser scanning point clouds acquired around the chimney to estimate vertical deviations with millimeter-level precision. Horizontal slices derived from the point cloud allows us to inspect the geometry of the chimney at different heights. Two methods able to estimate the center at different levels are illustrated and discussed. A first solution is a manual approach that uses traditional CAD software, in which circle fitting is manually carried out through point cloud slices. The second method is instead automatic and provides not only center coordinates, but also statistics to evaluate metric quality. Two case studies are used to explain the procedures for the digital survey and the measurement of vertical deviations: the chimney in the old slaughterhouse of Piacenza (Italy), and the chimney in Leonardo Campus at Politecnico di Milano (Italy).

High resolution photon time-tagging lidar for atmospheric point cloud generation.

The application of time-correlated single photon counting hardware and techniques to atmospheric lidar is presented. The results establish the viability of adapting photon time-tagging techniques to atmospheric lidar systems, facilitating high-range resolution (millimeter-level precision) and dynamic system observing capabilities that address the variety of atmospheric scatterers often present in atmospheric lidar profiles. The technique is demonstrated through measurements made by a high repetition rate, low pulse energy, elastic scattering, photon counting lidar. Detection probabilities with a non-zero system dead-time are derived and tested using acquired data. Atmospheric point cloud generation and the statistical implications on data retrievals utilizing this approach are presented. The results show an ability to preserve backscattered intensities while generating photon detections at picosecond resolution from a variety atmospheric scatterers.

Nationwide Railway Monitoring Using Satellite SAR Interferometry

Satellite synthetic aperture radar interferometry (InSAR) has the capability to monitor railway tracks and embankments with millimeter-level precision over wide areas. The potential of detecting differential deformation along the tracks makes it one of the most powerful and economical means for monitoring the safety and stability of the infrastructure on a weekly basis. Yet, the mere capability to detect such small deformations is not sufficient for an operational application of the technique. Handling huge data volumes, homogenizing independent datasets, and the connection with expert knowledge to identify risk areas are challenges to overcome. Here, we use a probabilistic method for InSAR time series postprocessing to efficiently scrutinize the data and detect railway instability. Moreover, to detect high-strain segments of the railway, we propose a short-arc-based method to focus on localized differential deformation between nearby InSAR measurement points. Our approach is demonstrated over the entire railway network of the Netherlands, more than 3000 km long, using hundreds of Radarsat-2 acquisitions between 2010 and 2015, leading to the first satellite-based nationwide railway monitoring system.

A simplified and unified model of multi-GNSS precise point positioning

Additional observations from other GNSS s can augment GPS precise point positioning (PPP) for improved positioning accuracy, reliability and availability. Traditional multi-GNSS PPP model requires the estimation of inter-system bias (ISB) parameter. Based on the scaled sensitivity matrix (SSM) method, a quantitative approach for assessing parameter assimilation, we theoretically prove that the ISB parameter is not correlated with coordinate parameters and it can be assimilated into clock and ambiguity parameters. Thus, removing ISB from multi-GNSS PPP model does not affect coordinate estimation. Based on this analysis, we develop a simplified and unified model for multi-GNSS PPP, where ISB parameter does not need to be estimated and observations from different GNSS systems are treated in a unified way. To verify the new model, we implement the algorithm to the self-developed software to process 1year GPS/GLONASS data of 53 IGS (International GNSS Service) worldwide stations and 1month GPS/BDS data of 15 IGS MGEX (Multi-GNSS Experiment) stations. Two types of GPS/GLONASS and GPS/BDS combined PPP solution are performed, one is based on traditional model and the other implements the new model. RMSs of coordinate differences between the two type of solutions are few μm for daily static PPP and less than 0.02mm for GPS/GLONASS kinematic PPP in the North, East and Up components, respectively. Considering the millimeter-level precision of current GNSS PPP solutions, these statistics demonstrate equivalent performance of the two solution types.

A Multichannel High-Precision CMOS Time-to-Digital Converter for Laser-Scanner-Based Perception Systems

A multichannel time-to-digital converter (TDC) implemented with 0.35-μm complementary metal-oxide-semiconductor technology that uses a low-frequency crystal as reference and measures the time intervals with counter and delay line interpolation techniques is described. The multichannel measurement architecture provides information on the time intervals between several timing signals. The circuit can be used for laser time-of-flight distance measurements, e.g., where it can determine time intervals between a transmitted laser pulse and several reflected pulses and also pulsewidths or rise times, to compensate for the timing walk error. This paper shows how several measurement channels can be integrated into one TDC without losing the measurement performance. The circuit offers a measurement precision that is better than 8 ps and a measurement range of up to 74 μs. In terms of laser distance measurement, its performance is equivalent to millimeter-level precision within an 11-km range.

GPS-InSAR Data Integration Method and its Application

The powerful tool of GPS-InSAR integration is drawing more and more attention in deformation monitoring. This paper introduces firstly method of atmospheric corrections and orbit errors to InSAR images using GPS datas. Then, the scheme of GPS-InSAR data integrating is expounded, Finally, Analysis and examples prove that GPS and InSAR technology has highly complementary. On the one hand the GPS provides good approach for resolving sensitivity that the InSAR opposite to atmospheric parameters change and the orbit error correction, on the other hand, we can use GPS technology to raise the InSAR spatial resolution , and are able to monitor surface deformation in millimeter-level precision. Therefore, using GPS-InSAR integrated technology will break through the technical limitations of a single application. They play each of their respective advantages, which greatly improve the resolved capacity in space domain and time domain, so as to provide better services to monitor the surface deformation.

Impact of high resolution radar imagery on reservoir monitoring

Surface deformation monitoring provides unique data for observing and measuring the performance of producing hydrocarbon reservoirs, for Enhanced Oil Recovery (EOR) and for Carbon Capture and Storage (CCS). To this end, radar interferometry (InSAR), particularly multi-interferogram Persistent Scatterer (PS) techniques, such as PSInSAR™, are innovative, valuable and cost-effective tools. Depending on reservoir characteristics and depth, oil or gas production can induce surface subsidence or, in the cases of EOR and CCS, ground heave, potentially triggering fault reactivation and in some cases threatening well integrity. Mapping the surface effects of fault reactivation, due to either fluid extraction or injection, usually requires the availability of hundreds of measurement points per square km with millimeter-level precision, which is time consuming and expensive to obtain using traditional monitoring techniques, but can be readily obtained with InSAR data. Moreover, advanced InSAR techniques developed in the last decade are capable of providing millimeter precision, comparable to optical leveling, and a high spatial density of displacement measurements over long periods of time, without the need for installing equipment or otherwise accessing the study area. Until recently, a limitation to the application of InSAR was the relatively long revisiting time (24 or 35 days) of the previous generation of C-band satellites (ERS1-2, Envisat, Radarsat). However, a new generation of X-band radar satellites (TerraSAR-X and the COSMO-SkyMed constellation), which have been operational since 2008, are providing significant improvements. TerraSAR-X has a repeat cycle of 11 days, while the joint use of two sensors of the COSMO-SkyMed constellation have an effective repeat cycle of just 8 days. With the launch of the fourth satellite of the constellation, in 2010, COSMO-SkyMed will have an effective revisiting time of just 4 days, allowing “near real-time” applications. Indeed, by combining two acquisition geometries (e.g. data acquired along ascending and descending orbits), it will be possible, on average, to have a new scene over the area of interest every other day. Additional advantages of the new X-band satellites are: A higher sensitivity to target displacement and a higher spatial resolution (the density of measurement points can be increased by an order of magnitude, possibly exceeding 2,500 PS/km2). In this paper, we present some examples of the application of X-band SAR data to reservoir monitoring. Special attention will be given to CCS projects where InSAR data could become a “standard” monitoring tool. The paper will highlight the technical features of the new sensors, the possible synergy between TerraSAR-X and COSMOSkyMed data, as well as the importance of a careful analysis of atmospheric disturbances affecting SAR data covering the area of interest, in order to retrieve high quality displacement data. Finally, some conclusions will be drawn supporting recommendations about future CCS monitoring programs.

Integer ambiguity resolution in precise point positioning: method comparison

Integer ambiguity resolution at a single receiver can be implemented by applying improved satellite products where the fractional-cycle biases (FCBs) have been separated from the integer ambiguities in a network solution. One method to achieve these products is to estimate the FCBs by averaging the fractional parts of the float ambiguity estimates, and the other is to estimate the integer-recovery clocks by fixing the undifferenced ambiguities to integers in advance. In this paper, we theoretically prove the equivalence of the ambiguity-fixed position estimates derived from these two methods by assuming that the FCBs are hardware-dependent and only they are assimilated into the clocks and ambiguities. To verify this equivalence, we implement both methods in the Position and Navigation Data Analyst software to process 1 year of GPS data from a global network of about 350 stations. The mean biases between all daily position estimates derived from these two methods are only 0.2, 0.1 and 0.0 mm, whereas the standard deviations of all position differences are only 1.3, 0.8 and 2.0 mm for the East, North and Up components, respectively. Moreover, the differences of the position repeatabilities are below 0.2 mm on average for all three components. The RMS of the position estimates minus those from the International GNSS Service weekly solutions for the former method differs by below 0.1 mm on average for each component from that for the latter method. Therefore, considering the recognized millimeter-level precision of current GPS-derived daily positions, these statistics empirically demonstrate the theoretical equivalence of the ambiguity-fixed position estimates derived from these two methods. In practice, we note that the former method is compatible with current official clock-generation methods, whereas the latter method is not, but can potentially lead to slightly better positioning quality.

Somatotopic blocking of sensation with navigated transcranial magnetic stimulation of the primary somatosensory cortex

We demonstrate that spatially accurate and selective stimulation is crucial when cortical functions are studied by the creation of temporary lesions with transcranial magnetic stimulation (TMS). Previously, the interpretation of the TMS results has been hampered by inaccurate knowledge of the site and strength of the induced electric current in the brain. With a Navigated Brain Stimulation (NBS) system, which provides real-time magnetic resonance image (MRI)-guided targeting of the TMS-induced electric field, we found that TMS of a spatially restricted cortical S1 thenar area is sufficient to abolish sensation from a weak electric stimulation of the corresponding skin area. We demonstrate that with real-time navigation, TMS can be repeatably directed at millimeter-level precision to a target area defined on the MRI. The stimulation effect was temporally and spatially specific: the greatest inhibition of sensation occurred when TMS was applied 20 ms after the cutaneous test stimulus and the TMS effect was sensitive to 8-13 mm displacements of the induced electric field pattern. The results also indicate that TMS selectively to S1 is sufficient to abolish perception of cutaneous stimulation of the corresponding skin area.