In this article, a cooperative multitechnology simultaneous localization and signal mapping (CM-SLASM) technique is proposed to improve the signal map accuracy and to build on-the-fly a signal map to ...be used also in indoor environments where conditions can change over time. Moreover, the CM-SLASM combines wireless fidelity (WiFi), ultra wideband (UWB), and light detection and ranging (LIDAR) signals to improve positioning estimation by sharing information and cooperation among vehicles through vehicle-to-vehicle (V2V) communication links. In particular, LIDAR-based distance between vehicles is shared among neighbor vehicles to improve the vehicle positioning estimated by an extended Kalman filter (EKF) where WiFi fingerprinting is combined with UWB multilateration. The overall solution where EKF estimation allows to building of more precise signal MAP is validated by simulation in a defined indoor scenario where vehicles equipped with different percentages of LIDAR, and different quantities of UWB and WiFi emitters have been considered. The proposed strategy has been validated through an extensive simulation campaign in various scenarios of interest and through a real-world experiment conducted in a laboratory test environment.
Bayesian Multilateration Alencar, Alisson S. C.; Mattos, Cesar L. C.; Gomes, Joao P. P. ...
IEEE signal processing letters,
2022, Letnik:
29
Journal Article
Recenzirano
Odprti dostop
Multilateration (MLAT) is the de facto technique to localize points of interest (POIs) in navigation and surveillance systems. Despite sensors being inherently noisy, most existing techniques i) are ...oblivious to noise patterns in sensor measurements; and ii) only provide point estimates of the POI. This often results in unreliable estimates with high variance, i.e ., that are highly sensitive to measurement noise. To overcome this caveat, we advocate the use of Bayesian modeling. Using Bayesian statistics, we provide a comprehensive guide to handle uncertainties in MLAT, including principled choices for the likelihood function and the prior distributions. Notably, the resulting model is easy to implement and can leverage off-the-shelf Markov Chain Monte Carlo (MCMC) software for inference. Besides coping with unreliable measurements, our framework can also deal with sensors whose location is not completely known, which is an asset in mobile systems. Our solution also naturally incorporates multiple measurements per reference point, a common practical situation that is usually not handled directly by other approaches. Comprehensive experiments with both synthetic and real-world data indicate that our Bayesian approach to the MLAT task provides better position estimation and uncertainty quantification when compared to the available alternatives.
Smart lighting systems have become indispensable in contemporary buildings, yet their configuration remains a laborious and time-consuming manual process, particularly in large spaces. As these ...systems grow increasingly vital, the need for efficient and automated configuration methods becomes clear. This study introduces a novel approach to streamline the smart lighting systems configuration process by using the Received Signal Strength Indicator (RSSI) data broadcasted by the luminaires via Bluetooth Low Energy (BLE), along with illuminance measurements from their visible light sensors to automate luminaire localization. An iterative localization process is proposed, based on a path loss propagation model for distance estimation, an adapted multilateration algorithm using RSSI measurements, and the estimation of proximity relationships among luminaires using illuminance measurements. Through real-world experiments, our approach showcases the potential for substantial time savings during commissioning, achieving a success rate exceeding 90% in accurately positioning luminaires.
The paper proposes an improved method for calculating the position of a movable tag whose distance to a (redundant) set of fixed beacons is measured by some suitable physical principle (typically ...ultra wide band or ultrasound propagation). The method is based on the multilateration technique, where the contribution of each individual beacon is weighed on the basis of a recurring, self-supported calibration of the measurement repeatability of each beacon at a given distance range. The work outlines the method and its implementation, and shows the improvement in measurement quality with respect to the results of a commercial Ultra-Wide-Band (UWB) system when tested on the same set of raw beacon-to-tag distances. Two versions of the algorithm are proposed: one-dimensional, or isotropic, and 3D. With respect to the standard approach, the isotropic solution managed to reduce the maximum localization error by around 25%, with a maximum error of 0.60 m, while the 3D version manages to improve even further the localization accuracy, with a maximum error of 0.45 m.
•Influence of commercial laser tracker in volumetric verification.•Self calibration techniques of laser trackers.•Different ways of applying multialterarion with laser tracker.•Influences of ...measurement noise in volumetric verification.•The influence of laser tracker positioning.
This paper aims to present different techniques and factors that affect the measurement accuracy of a commercial laser tracker responsible for capturing checkpoints used in machine tool volumetric verification. This study was conducted to uncover various sources of error affecting the measurement uncertainty of the laser tracker, additional sources of error that further contributed to the uncertainty, and the factors influencing these techniques. We also define several noise reduction techniques for the measurements.
The improvement in the accuracy of captured points focuses on a multilateration technique and its various resolution methods both analytically and geometrically. Similarly, we present trilateration and least squares techniques that can be used for laser tracker self-calibration, which is an essential parameter in multilateration.
This paper presents the influence of the spatial distribution of laser trackers (LTs) in measurement noise reduction by multilateration, which produces an improvement in volumetric error machine tool reduction. A study of the spatial angle between LTs, the distance and the visibility of the point to be measured are presented using a synthetic test. All of these factors limit the scope of multilateration. Similarly, a comparison of self-calibration techniques using the least squares and trilateration methods with which to determine the relative position of the laser tracker employees is presented. We also present the influence of the relationship between the radial and angular measurement noise self-calibration processes as it relates to the volumetric error reduction achieved by the machine tool with multilateration. All studies were performed using synthetic tests generated using a synthetic data parametric generator.
User location is becoming an increasingly common and important feature for a wide range of services. Smartphone owners increasingly use location-based services, as service providers add ...context-enhanced functionality such as car-driving routes, COVID-19 tracking, crowdedness indicators, and suggestions for nearby points of interest. However, positioning a user indoors is still problematic due to the fading of the radio signal caused by multipath and shadowing, where both have complex dependencies on the indoor environment. Location fingerprinting is a common positioning method where Radio Signal Strength (RSS) measurements are compared to a reference database of previously stored RSS values. Due to the size of the reference databases, these are often stored in the cloud. However, server-side positioning computations make preserving the user's privacy problematic. Given the assumption that a user does not want to communicate his/her location, we pose the question of whether a passive system with client-side computations can substitute fingerprinting-based systems, which commonly use active communication with a server. We compared two passive indoor location systems based on multilateration and sensor fusion using an Unscented Kalman Filter (UKF) with fingerprinting and show how these may provide accurate indoor positioning without compromising the user's privacy in a busy office environment.
Multilateration tracking systems (MLTSs) are used in industrial three-dimensional (3D) coordinate measuring applications. For high-precision measurement, system parameters must be calibrated properly ...in advance. For an MLTS using absolute distance measurement (ADM), the conventional self-calibration method significantly reduces estimation efficiency because all system parameters are estimated simultaneously using a complicated residual function. This paper presents a novel self-calibration method that optimizes ADM to reduce the number of system parameters via highly precise and separate estimations of dead paths. Therefore, the residual function to estimate the tracking station locations can be simplified. By applying a suitable mathematical procedure and solving the initial guess problem without the aid of an external device, estimation accuracy of the system parameters is significantly improved. In three self-calibration experiments, with ADM repeatability of approximately 3.4 µm, the maximum deviation of the system parameters estimated by the proposed self-calibration method was 68.6 µm, while the maximum deviation estimated by the conventional self-calibration method was 711.9 µm. Validation of 3D coordinate measurements in a 1000 mm × 1000 mm × 1000 mm volume showed good agreement between the proposed ADM-based MLTS and a commercial laser tracker, where the maximum difference based on the standard deviation was 17.7 µm. Conversely, the maximum difference was 98.8 µm using the conventional self-calibration method. These results confirmed the efficiency and feasibility of the proposed self-calibration method.
In this paper, we present an aircraft localization solution developed in the context of the Aircraft Localization Competition and applied to the OpenSky Network real-world ADS-B data. The developed ...solution is based on a combination of machine learning and multilateration using data provided by time synchronized ground receivers. A gradient boosting regression technique is used to obtain an estimate of the geometric altitude of the aircraft, as well as a first guess of the 2D aircraft position. Then, a triplet-wise and an all-in-view multilateration technique are implemented to obtain an accurate estimate of the aircraft latitude and longitude. A sensitivity analysis of the accuracy as a function of the number of receivers is conducted and used to optimize the proposed solution. The obtained predictions have an accuracy below 25 m for the 2D root mean squared error and below 35 m for the geometric altitude.
Indoor positioning systems can offer several benefits in various settings by providing real-time location data of assets and personnel. However, their widespread adoption is currently hindered by ...insufficient accuracy during deployment, which is caused by deterioration in signal quality due to clutter and wireless interference in the environment. The traditional localization techniques employed by off-the-shelf systems make use of simple algorithms that perform unsatisfactorily when dealing with real-life signals obtained in the actual environment. In the case of multilateration via Weighted Path Loss (WPL), the affected stages would be the beacon selection, distance estimation, and weights calculation subtasks. If beacons are selected purely on signal strength alone without regard for Geometric Dilution of Precision (GDOP), the chosen set can contribute to large estimation errors. Next, the usage of signals attenuated due to multipath effects and occlusion result in high error when they are converted into distance. Lastly, the weights calculation is based on the proportion of the converted distances, which can have an undesirable effect where beacons farther away exert undue influence over the calculated positioning estimate. Hence, in this work, an augmented WPL pipeline that uses GDOP for beacon selection and machine learning modules for distance estimation and weights calculation is proposed. Quantitative and qualitative findings from experimental trials show that this proposed augmented WPL pipeline can outperform its traditional counterpart and help it overcome its inherent limitations.
Indoor location and positioning systems (ILPS) are used to locate and track people, as well as mobile and/or connected targets, such as robots or smartphones, not only inside buildings with a lack of ...global navigation satellite systems (GNSS) signals but also in constrained outdoor situations with reduced coverage. Indoor positioning applications and their interest are growing in certain environments, such as commercial centers, airports, hospitals or factories. Several sensory technologies have already been applied to indoor positioning systems, where ultrasounds are a common solution due to its low cost and simplicity. This work proposes a 3D ultrasonic local positioning system (ULPS), based on a set of three asynchronous ultrasonic beacon units, capable of transmitting coded signals independently, and on a 3D mobile receiver prototype. The proposal is based on the aforementioned beacon unit, which consists of five ultrasonic transmitters oriented towards the same coverage area and has already been proven in 2D positioning by applying hyperbolic trilateration. Since there are three beacon units available, the final position is obtained by merging the partial results from each unit, implementing a minimum likelihood estimation (MLE) fusion algorithm. The approach has been characterized, and experimentally verified, trying to maximize the coverage zone, at least for typical sizes in most common public rooms and halls. The proposal has achieved a positioning accuracy below decimeters for 90% of the cases in the zone where the three ultrasonic beacon units are available, whereas these accuracies can degrade above decimeters according to whether the coverage from one or more beacon units is missing. The experimental workspace covers a large volume, where tests have been carried out at points placed in two different horizontal planes.
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