Position Estimation Research Articles

On the Integration of Standard Deviation and Clustering to Promote Scalable and Precise Wi-Fi Round-Trip Time Positioning

Recently, the use of fingerprinting has been proposed for positioning using the Wi-Fi RTT estimations gathered by IEEE 802.11mc devices. Wi-Fi RTT poses a challenge on scalability due to the location-specific traffic injected in the network, which may limit the data traffic transmissions of other Wi-Fi users. In this respect, fingerprinting has been regarded as a promising scalable technique, compared to multilateration. While coupling other metrics should bring relief to the system, reducing the number of APs to which RTT measurements are requested alleviates the burden in specific cells. But how far may we go? This paper assesses several methods aimed at reducing the Wi-Fi RTT overhead while preserving the precision of the calculated position. The use of the Wi-Fi RTT standard deviation is assessed for the first time, being especially useful when the number of RTT procedures is minimized. The application of clustering can also improve position estimates while leveraging bandwidth for other users’ purposes.

Relative position estimation using modulated magnetic field for close proximity formation flight

This paper presents a method to estimate relative position vectors between spacecraft equipped with magnetic coils and magnetic field sensors for close proximity operation. Filters can segregate a magnetic field with a particular frequency if spacecraft drive their coils with this specific frequency. The proposed method utilizes the amplitude of the magnetic field with a particular frequency to estimate relative position vectors. The method consists of an initial position estimator and a sequential position estimator, which is an unscented Kalman filter. The initial position estimator provides a coarse estimate for the relative position vectors using the segregated magnetic field. Relation between the magnetic field and relative position vector is derived analytically in this article for the initial position estimator. The unscented Kalman filter refines the estimation accuracy by initializing the filter with the estimate by the initial position estimator. It is shown that a spacecraft can conduct relative position vector estimation using the magnetic field of a target spacecraft, provided that a few conditions clarified in the article are satisfied. Finally, the proposed estimators are evaluated numerically via simulations.

A correlation-based approach for fast prediction of the equilibrium position of particles within a spiral microchannel

ABSTRACT As inertial microfluidics is a proven technique for manipulating particles within microchannels, a deep understanding of hydrodynamics forces acting on particles in these systems is crucial for optimal manipulation. However, existing numerical techniques for examining particle equilibrium positions are often time-intensive and require high-memory systems, limiting accessibility due to complexity and cost. To address this issue, this study proposes a method to develop a correlation for fast estimation of particle equilibrium positions. An algorithm is devised to develop the correlation in three main steps: first, a dataset is created by conducting simulations using the finite element method, considering width, height, flow rate, particle size, and curvature radius. The computed distance between the equilibrium position of the particle and the inner channel wall serves as input for the next step where a general form of the correlation is established using Buckingham’s Π-theorem. The unknown coefficients of the correlation are calculated using 80 percent of the dataset from the first step and the least sum squares errors method. Finally, the obtained correlation is validated using the remaining data and previous experimental studies. The proposed correlation reduces the computational burden associated with predicting particle focus positions, with a 3.7 percent mean absolute error.

An INS/UWB fusion localization scheme for wireless sensor network

Abstract As the demand for indoor services relying on location information grows, achieving precise indoor positioning is becoming an urgent issue to address. The ultra-wide band (UWB) accuracy can reach centimeter level, but is susceptible to non-line-of-sight (NLOS) effects. The inertial navigation system (INS) is not affected by the environment, but the error will diverge over time. Therefore, this paper focuses on the UWB/INS combined positioning system, which can combine the advantages of both. We propose a loosely-coupled INS/UWB indoor localization scheme based on factor graph optimization (FGO). Firstly, an agglomerative hierarchical clustering based NLOS mitigation method is applied to preprocess the UWB raw measurement data. The position estimates under UWB are then obtained using an improved extended Kalman filter to mitigate NLOS errors and provide more accurate location data for combined navigation. Then, we build the IMU preintegration factor and the zero-bias factor. Finally, FGO is used to fuse the information to get the final location. Designed experiments demonstrate the superiority of the algorithm. The simulation and experimental results show that the proposed scheme outperforms the comparison algorithms.

Fingerprint localisation for fine‐scale wildlife tracking using automated radio telemetry

Abstract Automated radio telemetry systems are one of the most widely applicable methods for tracking wildlife at fine spatiotemporal scales. A growing trend is for these systems to apply large networks of receivers to detect radio signal strength (RSS) from radio‐tagged individuals. Analytical methods to derive position estimates using RSS localisation, however, are relatively underdeveloped in the field of wildlife tracking. Here, we apply approaches from indoor positioning systems to develop a new method, radio fingerprinting, for localising radio‐tagged animals in structurally complex, outdoor environments. This method characterises the RSS patterns at known locations to generate a radio map of the study area, which is then used to predict the location of new RSS patterns. We conducted field tests to evaluate the localisation accuracy of radio fingerprinting relative to multilateration, a commonly used method for RSS localisation. To do so, we established an experimental receiver network covering multiple habitat types and compared the localisation accuracy of radio fingerprinting to multilateration. Additionally, we evaluated how a variety of features characteristic of typical tracking data sets affected the accuracy of both methods. While both methods had a similar median error under ideal conditions (~30 m), radio fingerprint localisation method offered several advantages over multilateration. Multilateration localisation estimates were highly affected by missed detections from the nearest receiver to the test point, which occurred in 30% of cases. In these cases, the median error was 103 m, over a 3.5‐fold increase. Distance to the nearest receiver also biased multilateration estimates with error increasing as the distance increased. Additionally, errors from multilateration estimates were higher in more densely vegetated areas. In contrast, fingerprinting position estimates were largely robust to each of these scenarios. Automated radio telemetry enables the fine‐scale, continuous tracking of range‐resident animals. We present radio fingerprinting as a localisation method in outdoor environments where standard localisation methods are error‐prone due to habitat heterogeneity and missed detections. This approach can be applied to any automated radio telemetry hardware and to any study system where a radio map can be generated.

Accurate Low Complexity Quadrature Angular Diversity Aperture Receiver for Visible Light Positioning.

Despite the many potential applications of an accurate indoor positioning system (IPS), no universal, readily available system exists. Much of the IPS research to date has been based on the use of radio transmitters as positioning beacons. Visible light positioning (VLP) instead uses LED lights as beacons. Either cameras or photodiodes (PDs) can be used as VLP receivers, and position estimates are usually based on either the angle of arrival (AOA) or the strength of the received signal. Research on the use of AOA with photodiode receivers has so far been limited by the lack of a suitable compact receiver. The quadrature angular diversity aperture receiver (QADA) can fill this gap. In this paper, we describe a new QADA design that uses only three readily available parts: a quadrant photodiode, a 3D-printed aperture, and a programmable system on a chip (PSoC). Extensive experimental results demonstrate that this design provides accurate AOA estimates within a room-sized test chamber. The flexibility and programmability of the PSoC mean that other sensors can be supported by the same PSoC. This has the potential to allow the AOA estimates from the QADA to be combined with information from other sensors to form future powerful sensor-fusion systems requiring only one beacon.

Position estimation of acoustic elements based on improved delay estimation algorithm

Array signal processing is extensively utilized in the field of underwater acoustics (UWA). The majority of existing array signal processing algorithms require precise array position information to optimize their functionality. However, the intricate nature of the UWA environment introduces challenges such as the influence of water flow, which may result in deviations from the predetermined array positions. Consequently, this can amplify errors in array processing algorithms. Therefore, a high-precision array positioning method is needed to estimate the actual position of the array. The effectiveness of current array localization algorithms employing delay differential matching depends significantly on the accuracy of delay estimation and the formulation of the ambiguity function. In response to these crucial factors, this paper presents an algorithm for estimating array element positions that leverages an improved approach to delay estimation. Firstly, we propose the ρ-PHAT algorithm enhanced by the artificial fish swarm algorithm (AFSA-PHAT), significantly improving delay estimation accuracy, particularly in low signal-to-noise ratio (SNR) conditions. Compared to the traditional ρ-PHAT algorithm, this approach achieves a 3 dB increase in precision and a reduction in the root-mean-square error (RMSE). Additionally, a novel method is introduced for constructing the ambiguity function, which focuses on minimizing the acoustic complexity to encompass only direct and surface-reflected sounds. This improvement makes it particularly suitable for hydrophone arrays deployed near the sea surface. Computer simulations and experimental results validate that the algorithm, incorporating the aforementioned improvements, achieves enhanced accuracy in position estimation, reduced RMSE, and increased robustness.

Visual-Inertial RGB-D SLAM with Encoder Integration of ORB Triangulation and Depth Measurement Uncertainties.

In recent years, the accuracy of visual SLAM (Simultaneous Localization and Mapping) technology has seen significant improvements, making it a prominent area of research. However, within the current RGB-D SLAM systems, the estimation of 3D positions of feature points primarily relies on direct measurements from RGB-D depth cameras, which inherently contain measurement errors. Moreover, the potential of triangulation-based estimation for ORB (Oriented FAST and Rotated BRIEF) feature points remains underutilized. To address the singularity of measurement data, this paper proposes the integration of the ORB features, triangulation uncertainty estimation and depth measurements uncertainty estimation, for 3D positions of feature points. This integration is achieved using a CI (Covariance Intersection) filter, referred to as the CI-TEDM (Triangulation Estimates and Depth Measurements) method. Vision-based SLAM systems face significant challenges, particularly in environments, such as long straight corridors, weakly textured scenes, or during rapid motion, where tracking failures are common. To enhance the stability of visual SLAM, this paper introduces an improved CI-TEDM method by incorporating wheel encoder data. The mathematical model of the encoder is proposed, and detailed derivations of the encoder pre-integration model and error model are provided. Building on these improvements, we propose a novel tightly coupled visual-inertial RGB-D SLAM with encoder integration of ORB triangulation and depth measurement uncertainties. Validation on open-source datasets and real-world environments demonstrates that the proposed improvements significantly enhance the robustness of real-time state estimation and localization accuracy for intelligent vehicles in challenging environments.

An investigation of PPP-B2b coverage and its performance in ZTD estimation and positioning in different regions

This study comprehensively evaluates the Beidou navigation satellite system's PPP-B2b service for real-time positioning and zenith total delay (ZTD) estimation. Despite its operational status, PPP-b2b's effective coverage is underexplored. We define this coverage by analysing satellite visibility and geometry and evaluating ZTD and positioning accuracy at 48 stations. Results show PPP-B2b achieves ZTD Errors of 10–20 mm in China and 15–30 mm in Europe, with kinematic experiments in China and Japan showing consistent accuracy within 20 mm. This study highlights PPP-b2b's potential for enhancing atmospheric monitoring and precise positioning in its effective regions.

Doping position estimation for FeRh-based alloys

FeRh-based alloys have attracted significant attention due to their magnetic phase transition and significant magnetocaloric effects. These properties position them as promising candidates for fundamental research and practical applications, including magnetic cooling and targeted drug delivery. The study of FeRh alloys, particularly those where Rhodium or Iron atoms are substituted with other transition metals, is crucial as certain substitutions preserve the alloy’s magnetocaloric properties. However, even within a specific structural type and without considering competing phases, determining which atom (Fe or Rh) is replaced upon introducing a third element remains unclear. This paper addresses this ambiguity through ab initio calculations. We propose an approach to predict whether a dopant will replace Fe or Rh, offering insights into the electronic and structural factors influencing the substitution. Additionally, we present a dataset of ab initio calculations on doped FeRh alloys, which will support future data-driven modeling efforts. Our findings not only advance the understanding of FeRh-based alloys but also contribute to the design of novel materials for experimental and industrial applications.

Drone Swarm Robust Cooperative Formation Pursuit through Relative Positioning in a Location Denial Environment

This paper considers the pursuit problem of a moving target by a swarm of drones through a flexible-configuration formation. The drones are modeled by second-order systems subject to uncertain damping ratios, whereas the moving target follows a polynomial-type trajectory whose coefficient vectors are fully unknown. Due to location denial, drones cannot obtain their absolute positions, but they can obtain their positions relative to other neighboring drones and the target. To achieve a robust formation pursuit, a robust cooperative control protocol is synthesized, which comprises three key components, namely, the pseudo drone position estimator, the pseudo target position estimator, and the local internal model control (IMC) law. The pseudo drone position estimator and the pseudo target position estimator aim to recover for each drone the position of itself and the target, respectively, but are subject to some common unknown constant bias in a distributed manner. By subtracting the pseudo target position from the pseudo drone position, each drone can acquire its position relative to the target, which facilitates the design of a local IMC law to fulfill formation pursuit in the presence of system parametric uncertainties. Both pure numerical simulation and hardware-in-the-loop (HIL) simulation are performed to verify the effectiveness of the proposed control protocol.

Ratio of Stem Wood Volumes in Forest Stands and Dead Wood of the Taiga Spruce Forests in European Russia

The article discusses the formation of the stem wood volumes ratio between the forest stands and the deadwood in an indigenous forest community with a contribution from wood-decaying fungi, using the spruce formations of the European Russia’s taiga zone as an example. For the analysis, 30 spruce ecosystems were taken, 10 in each of the taiga subzones (northern, middle and southern) with different dynamic characteristics — climax, demutational and digressional ecosystems. Using the method of study plots (SP), the silvicultural characteristics of ecosystems and the morphometric indicators of trees were described, and the volumes of stem wood of the forest stands forming phytocenoses and the deadwood decomposed by wood-destroying fungi were calculated. Indicators of the stem wood volumes ratio between the forest stands and the dead wood in spruce plantations of various dynamic phases were calculated, for which phase position scores were calculated. Indicators of the relationship between the volumes of stem wood in forest stands and in dead wood (R2)and linear correlation coefficients (r) for forest stands of different successional positions were determined in Microsoft Excel. The calculations confirmed the presence of a relationship between the stem wood volumes of tree stands and deadwood for the studied spruce forests using a point estimate of the phase position of ecosystems: in both programs (R2 and r) the relationship indicators were characterized as strong to very strong (Chaddock, 1925).

Indoor Person Position Estimation with Channel State Information with Privacy Consideration

Indoor Person Position Estimation with Channel State Information with Privacy Consideration

Sensorless Predictive Control With Fusion Position Estimation Technology for PMSM Drives

Sensorless Predictive Control With Fusion Position Estimation Technology for PMSM Drives

An Accurate Full-Speed Position Estimation for Permanent Magnet Synchronous Motors With a DC-Bus Current Sensor

An Accurate Full-Speed Position Estimation for Permanent Magnet Synchronous Motors With a DC-Bus Current Sensor

On the Integration of VLBI Observations to GENESIS into Global VGOS Operations

The upcoming European Space Agency (ESA) satellite mission GENESIS is an Earth-orbiting satellite carrying instruments of all four space geodetic techniques. The onboard transmitter for Very Long Baseline Interferometry (VLBI) will allow the observation of the satellite with VLBI radio telescopes. The objective of this study is to investigate the integration of VLBI observations of GENESIS into the operations of the VLBI Global Observing System (VGOS). Based on both current and foreseeable modern VGOS antenna networks, we consider the realistic observability of both geodetic radio sources and GENESIS. We conduct a comprehensive scheduling and perform extensive simulations of the VLBI observations. We assume that observations of GENESIS are scheduled within regular, geodetic experiments. The integration of GENESIS as an additional source in the scheduling results in a minimal degradation in the geodetic parameter estimation of station positions and dUT1 of less than 0.09 mm and 0.06 μs, respectively. The results suggest to schedule scans of GENESIS at intervals of about 5 min to limit the decrease in the number of observations of geodetic sources to less than 5% with respect to schedules containing only geodetic radio sources. The schedules for 24 h experiments comprise about 150 to 200 scans and 1000 to 5000 observations of GENESIS, depending on the size of the utilized network. The frame tie accuracy between the VLBI and GENESIS frames is assessed in the form of station positions, which are solely estimated from observations of GENESIS. Multiple 24 h experiments are simulated over 52 weeks with assumed session cadences of two to three experiments per week. By stacking the normal equations from three months of experiments, we obtain station position estimates with a precision of less than 10 mm. After 12 months, the repeatabilites are reduced to less than 5 mm.

Full-speed domain position sensorless control strategy for PMSM based on a novel phase-locked loop

This paper proposes a full-speed-domain position-sensor-less control strategy for precise control under forward and reverse rotation conditions to address the weak convex polarity of surface-mounted permanent magnet synchronous motor (SPMSM). The strategy comprises several key stages: pre-positioning of the rotor, constant current variable frequency (I/F) start-up, construct the Luenberger State Observer, and utilization of an improved phase-locked loop (PLL) for position estimation. In the pre-positioning stage, a constant amplitude current is applied to drag the rotor to a predetermined position. Subsequently, the I/F start-up stage accelerates the motor to a predetermined speed before transitioning to the Luenberger observer for closed-loop speed control, which is based on an extended back electromotive force (back-EMF) a two-phase rotating coordinate system. The improved PLL for position and speed estimation features three components: a phase discriminator (PD), a voltage-controlled oscillator (VCO), and loop filter (LF). Experimental results demonstrate the efficacy of the proposed strategy, showing quick start-up response, speed estimation error below 2 RPM, rotor position estimation error under 0.6 degrees post-loop closure, stable tracking during rapid speed changes, and consistent accuracy and stability even under reverse rotation conditions, thereby meeting the control strategy’s objectives.

Gelatinous filter feeders increase ecosystem efficiency

Gelatinous filter feeders (e.g., salps, doliolids, and pyrosomes) have high filtration rates and can feed at predator:prey size ratios exceeding 10,000:1, yet are seldom included in ecosystem or climate models. We investigated foodweb and trophic dynamics in the presence and absence of salp blooms using traditional productivity and grazing measurements combined with compound-specific isotopic analysis of amino acids estimation of trophic position during Lagrangian framework experiments in the Southern Ocean. Trophic positions of salps ranging 10–132 mm in size were 2.2 ± 0.3 (mean ± std) compared to 2.6 ± 0.4 for smaller (mostly crustacean) mesozooplankton. The mostly herbivorous salp trophic position was maintained despite biomass dominance of ~10-µm-sized primary producers. We show that potential energy flux to >10-cm organisms increases by approximately an order of magnitude when salps are abundant, even without substantial alteration to primary production. Comparison to a wider dataset from other marine regions shows that alterations to herbivore communities are a better predictor of ecosystem transfer efficiency than primary-producer dynamics. These results suggest that diverse consumer communities and intraguild predation complicate climate change predictions (e.g., trophic amplification) based on linear food chains. These compensatory foodweb dynamics should be included in models that forecast marine ecosystem responses to warming and reduced nutrient supply.

Predicting Signal Reception Information from GNSS Satellites in Indoor Environments without Site Survey: Towards Opportunistic Indoor Positioning Based on GNSS Fingerprinting

While traditional GPS localization is impractical in certain indoor environments, GPS satellites offer a valuable source of indoor contextual information, particularly around window-side areas where signals are more accessible. This study introduces a new method that predicts GPS signal reception information in a target indoor environment without the need for actual data collection in the target environment. By predicting the strengths of GPS signals that are expected to be measured at various indoor positions, we can construct a GPS signal reception map of a target environment, which functions similarly to a Wi-Fi fingerprinting map surrounding window-side areas, offering a new dimension in indoor positioning systems. For instance, it aids in the correction of accumulated errors in pedestrian dead reckoning (PDR) systems. Our proposed method leverages easily accessible inputs, including satellite location data, indoor floorplan image of the target floor, and 3D mapping of the surrounding buildings, to predict signal reception at each position in the target environment. We developed a specialized neural network, named multi-scale branch fusion network (MSBF-Net), designed to process and integrate data of varying scales, such as the floorplan image of the target environment and 3D map of the surrounding area obtained from Google Earth, with a specific focus on understanding the line-of-sight (LOS) and multi-path effects caused by internal obstacles and surrounding buildings. This advanced capability enables the network to effectively interpret complex signal interactions within urban environments, enhancing its predictive accuracy for GPS signal reception. The effectiveness of our method was rigorously evaluated using real-world environments. In addition, we employed our method to implement opportunistic GPS fingerprint-based indoor positioning, where position estimates are provided when a strong signal is observed from at least one satellite. Surprisingly, the positioning method achieved a positioning error of only 2.8 meters when a smartphone is close to window-side areas even though the method does not rely on labeled training data collected in a target environment and signal infrastructures installed in the target environment.

DFT-spread OTFS-NOMA for downlink integrated positioning and communication

In this article, a non-orthogonal multiple-access (NOMA) transmission system that incorporates discrete Fourier transform (DFT) spread orthogonal time-frequency space (OTFS) modulation is proposed for the downlink integrated positioning and communication (IPAC). This system is designed to decrease the Peak-to-Average Power Ratio (PAPR) within the OTFS-NOMA system while simultaneously serving both communication user (CU) and positioning user (PU) within the same time-frequency resources. Firstly, we demonstrate the applicability of the proposed DFT-spread OTFS-NOMA (DFT-s-OTFS-NOMA) system for downlink transmission. It efficiently serves both the CU and PU concurrently within the same time and frequency resources, thereby increasing spectrum utilization. Subsequently, we develop a two-stage parameter estimation algorithm focusing on accurate positioning parameter estimation for PU and precise channel estimation for CU. Then, the position of the PU is estimated using the time of arrival (TOA) model and the linear least squares (LLS) approach. Simulation demonstrates a 9 dB PAPR reduction in the proposed system compared to the existing OTFS-NOMA system. Additionally, the proposed two-stage positioning method for the PU achieves centimeter-level accuracy in position estimation and near millimeter-per-second-level accuracy in velocity estimation. What is more, the performance of channel estimation and symbol detection, aided by the PU signal in the DFT-s-OTFS-NOMA system, demonstrates resilience against Doppler effects without the need for reliance on pilots. This ensures sustained an effective Bit Error Rate (BER) even in time-variant high mobility scenarios.