A Constrained Kalman Filter for Wi-Fi-Based Indoor Localization with Flexible Space Organization

This paper presents a constrained Kalman filter for Wi-Fi-based indoor localization. The contribution of this work is to introduce constraints on the object speed and to provide a numerically optimized form for fast computation. The proposed approach is suitable to flexible space organization, as in warehouses, and when objects can be spun around, for example barcode readers in a hand. We experimented with the proposed technique using a robot and three devices, on five different journeys, in a 6000 m2 warehouse equipped with six Wi-Fi access points. The results highlight that the proposed approach provides a 19% improvement in localization accuracy.

A Cooperative Positioning Method of Connected and Automated Vehicles with Direction-of-Arrival and Relative Distance Fusion

The rapid development of science and technology has created favorable conditions for Connected and Automated Vehicles (CAVs). Accurate localization is one of the fundamental functions of CAV to realize some advanced operations such as vehicle platooning. However, complicated urban traffic environments, such as the flyover, significantly influence vehicular positioning accuracy. The inability of CAV to accurately perceive self-localization information has become an urgent issue to be addressed. This paper proposed a novel cooperative localization method by introducing the relative Direction-of-Arrival (DOA) and Relative Distance (RD) into CAV to improve the localization accuracy of CAV in the multivehicle environment. First, the three-dimensional positioning error model of the host vehicle concerning adjacent vehicles in azimuth angle and pitch angle and intervehicle distances under the vehicle-to-vehicle communication was established. Second, two least-squares estimation algorithms, linear and nonlinear, are established to decrease the position errors by combining relative DOA and RD measurement information. To verify the proposed algorithm's effect, the PreScan-Simulink joint simulation is carried out. The results show that the host vehicle's localization accuracy by the proposed method can be improved by 25% compared with direct linearization. Besides, by combining relative DOA and relative RD measurement, the locating capability of the least-square-based nonlinear optimization method can be enhanced by 22%.

Core point pixel-level localization by fingerprint features in spatial domain

<abstract> <p>Singular point detection is a primary step in fingerprint recognition, especially for fingerprint alignment and classification. But in present there are still some problems and challenges such as more false-positive singular points or inaccurate reference point localization. This paper proposes an accurate core point localization method based on spatial domain features of fingerprint images from a completely different viewpoint to improve the fingerprint core point displacement problem of singular point detection. The method first defines new fingerprint features, called furcation and confluence, to represent specific ridge/valley distribution in a core point area, and uses them to extract the innermost Curve of ridges. The summit of this Curve is regarded as the localization result. Furthermore, an approach for removing false Furcation and Confluence based on their correlations is developed to enhance the method robustness. Experimental results show that the proposed method achieves satisfactory core localization accuracy in a large number of samples.</p> </abstract>

Data-driven Expectations for Electromagnetic Counterpart Searches Based on LIGO/Virgo Public Alerts

Searches for electromagnetic counterparts of gravitational-wave signals have redoubled since the first detection in 2017 of a binary neutron star merger with a gamma-ray burst, optical/infrared kilonova, and panchromatic afterglow. Yet, one LIGO/Virgo observing run later, there has not yet been a second, secure identification of an electromagnetic counterpart. This is not surprising given that the localization uncertainties of events in LIGO and Virgo’s third observing run, O3, were much larger than predicted. We explain this by showing that improvements in data analysis that now allow LIGO/Virgo to detect weaker and hence more poorly localized events have increased the overall number of detections, of which well-localized, gold-plated events make up a smaller proportion overall. We present simulations of the next two LIGO/Virgo/KAGRA observing runs, O4 and O5, that are grounded in the statistics of O3 public alerts. To illustrate the significant impact that the updated predictions can have, we study the follow-up strategy for the Zwicky Transient Facility. Realistic and timely forecasting of gravitational-wave localization accuracy is paramount given the large commitments of telescope time and the need to prioritize which events are followed up. We include a data release of our simulated localizations as a public proposal planning resource for astronomers.

Auditory Subjective-Straight-Ahead Blurs during Significantly Slow Passive Body Rotation

This paper reports on the deterioration in sound-localization accuracy during listeners’ head and body movements. We investigated the sound-localization accuracy during passive body rotations at speeds in the range of 0.625–5 °/s. Participants were asked to determine whether a 30-ms noise stimuli emerged relative to their subjective-straight-ahead reference. Results indicated that the sound-localization resolution degraded with passive rotation, irrespective of the rotation speed, even at speeds of 0.625 °/s.

DAFI

WiFi-based Device-free Passive (DfP) indoor localization systems liberate their users from carrying dedicated sensors or smartphones, and thus provide a non-intrusive and pleasant experience. Although existing fingerprint-based systems achieve sub-meter-level localization accuracy by training location classifiers/regressors on WiFi signal fingerprints, they are usually vulnerable to small variations in an environment. A daily change, e.g., displacement of a chair, may cause a big inconsistency between the recorded fingerprints and the real-time signals, leading to significant localization errors. In this paper, we introduce a Domain Adaptation WiFi (DAFI) localization approach to address the problem. DAFI formulates this fingerprint inconsistency issue as a domain adaptation problem, where the original environment is the source domain and the changed environment is the target domain. Directly applying existing domain adaptation methods to our specific problem is challenging, since it is generally hard to distinguish the variations in the different WiFi domains (i.e., signal changes caused by different environmental variations). DAFI embraces the following techniques to tackle this challenge. 1) DAFI aligns both marginal and conditional distributions of features in different domains. 2) Inside the target domain, DAFI squeezes the marginal distribution of every class to be more concentrated at its center. 3) Between two domains, DAFI conducts fine-grained alignment by forcing every target-domain class to better align with its source-domain counterpart. By doing these, DAFI outperforms the state of the art by up to 14.2% in real-world experiments.

Effects of Visually Induced Self-Motion on Sound Localization Accuracy

The deterioration of sound localization accuracy during a listener’s head/body rotation is independent of the listener’s rotation velocity (Honda et al., 2016). However, whether this deterioration occurs only during physical movement in a real environment remains unclear. In this study, we addressed this question by subjecting physically stationary listeners to visually induced self-motion, i.e., vection. Two conditions—one with a visually induced perception of self-motion (vection) and the other without vection (control)—were adopted. Under both conditions, a short noise burst (30 ms) was presented via a loudspeaker in a circular array placed horizontally in front of a listener. The listeners were asked to determine whether the acoustic stimulus was localized relative to their subjective midline. The results showed that in terms of detection thresholds based on the subjective midline, the sound localization accuracy was lower under the vection condition than under the control condition. This indicates that sound localization can be compromised under visually induced self-motion perception. These findings support the idea that self-motion information is crucial for auditory space perception and can potentially enable the design of dynamic binaural displays requiring fewer computational resources.

Measurement of Lead Localization Accuracy Based on Magnetic Resonance Imaging

Post-implantation localization of deep brain stimulation (DBS) lead based on a magnetic resonance (MR) image is widely used. Existing localization methods use artifact center method or template registration method, which may lead to a considerable deviation of &gt; 2 mm, and result in severe side effects or even surgical failure. Accurate measurement of lead position can instantly inform surgeons of the imprecise implantation. This study aimed to identify the influencing factors in DBS lead post-implantation localization approach, analyze their influence, and describe a localization approach that uses the individual template method to reduce the deviation. We verified that reconstructing direction should be parallel or perpendicular to lead direction, instead of the magnetic field. Besides, we used simplified relationship between magnetic field angle and deviation error to correct the localization results. The mean localization error can be reduced after correction and favors the feasibility of direct localization of DBS lead using MR images. We also discussed influence of in vivo noise on localization frequency and the possibility of using only MR images to localize the contacts.

Anchor Density Minimization for Localization in Wireless Sensor Network (WSN)

In wireless sensor networks (WSN) high-accuracy localization is crucial for both of WNS management and many other numerous location-based applications. Only a subset of nodes in a WSN is deployed as anchor nodes with their locations a priori known to localize unknown sensor nodes. The accuracy of the estimated position depends on the number of anchor nodes. Obviously, increasing the number or ratio of anchors will undoubtedly increase the localization accuracy. However, it severely constrains the flexibility of WSN deployment while impacting costs and energy. This paper aims to drastically reduce anchor number or ratio of anchor in WSN deployment and ensures a good trade-off for localization accuracy. Hence, this work presents an approach to decrease the number of anchor nodes without compromising localization accuracy. Assuming a random string WSN topology, the results in terms of anchor rates and localization accuracy are presented and show significant reduction in anchor deployment rates from 32% to 2%.

Innovative Differential Magnetic Localization Method for Capsule Endoscopy to Prevent Interference Caused by the Geomagnetic Field

Wireless capsule endoscopy is an established medical application for the examination of the gastrointestinal tract. However, the robust and precise localization of these capsules is still in need of further scientific investigation. This paper presents an innovative differential magnetic localization method for capsule endoscopy to prevent interference caused by the geomagnetic field. The effect of changing the orientation of the capsule on the localization process was also examined. Simulations using COMSOL Multiphysics with the superimposed geomagnetic field were performed. The Levenberg–Marquardt algorithm was applied in MATLAB to estimate the position and orientation of the capsule. Comparing the proposed differential method with the absolute magnetic localization method under ideal conditions, the mean position and orientation errors were reduced by three orders in magnitude to less than 0.1 mm and 0.1∘ respectively. Even if sensor non-idealities are considered, the simulation-based results reveal that our proposed method is competitive with state-of-the-art geomagnetic compensation methods for static magnetic localization of capsule endoscopes. The achieved localization accuracy by applying the differential method is not dependent on the rotation of the localization system relative to the geomagnetic flux density under the made assumptions and the impact of the magnet orientation is neglectable. It is concluded that the proposed method is capable of preventing all interference whose components are approximately equal at all sensors with identical orientation.