Proposed Localization Scheme Research Articles

An analytical geometric range free localization scheme based on mobile beacon points in wireless sensor network

In many applications of wireless sensor network, the position of the sensor node is useful to identify the actuating response of the environment. The main idea of the proposed localization scheme i...

이중대역 AP를 이용한 LOS/NLOS 판별 및 실내 위치 측위 기술

With standardization of IEEE 802.11n, APs with the 2.4GHz and 5GHz dual-band capability have widely been deployed over a metropolitan area by individuals and internet service providers. Moreover, due to the increasing attentions on indoor-localization technique using Wi-Fi, the need for LOS and NLOS determination scheme is increasing to enhance accuracy of the localization. In this paper, we propose a novel LOS/NLOS determination technique by using different radio attenuation characteristics in different frequency bands and different mediums. Based on this technique, we designed a LOS/NLOS-aware indoor localization scheme. The proposed LOS/NLOS determination algorithm can be used when the distance between an user device and an AP is unknown, and the proposed localization scheme provides very accurate room-level position information. We validated the proposed scheme by implementing it on Android smart phones.

Indoor positioning via subarea fingerprinting and surface fitting with received signal strength

The fingerprinting technique based on received signal strength (RSS) has been intensively researched for indoor localization in the last decade. Instead of using discrete reference points to build fingerprint database, this paper applies the surface fitting technique to construct RSS spatial distribution functions and proposes two location search methods to find the target location. We also propose to use subarea division and determination scheme to improve the fitting accuracy and search efficiency. In the offline phase, we divide the whole indoor environment into several subareas, construct a fingerprint for each subarea, and build a RSS distribution fitting function for each access point in each subarea. In the online phase, we first determine to which subarea a target belongs, and then search its location according to the proposed exhaustive location search or gradient descent based search algorithm. We conduct both extensive simulations and field experiments to verify the proposed scheme. The experiment results show that for the same reference point granularity, the proposed localization scheme can achieve about 22% localization accuracy improvement, compared with the classical nearest neighbor-based fingerprinting method.

Underwater Sensor Network Positioning Using an AUV Moving on a Random Waypoint Path

ABSTRACTIn this paper, a range-free, passive, and autonomous underwater vehicle (AUV)-based localization scheme is proposed for underwater acoustic sensor networks. The AUV has used four directional acoustic beams with fixed steering angle and width, which led to the constant ratio of array size to wavelength, in order to localize the sensor nodes. The AUV was moved on a random waypoint path and broadcasted messages periodically. The sensor nodes used two successively received message sequences which were submitted by two beams on one side of the AUV path in order to localize themselves. Extensive simulation results in MATLAB demonstrated that using the proposed localization scheme could yield better localization success than other AUV-based localization methods.

Implant Position Estimation Via Wireless Power Link

Wireless power transmission is widely used in implantable medical devices (IMDs). Surgical placement of IMDs has limited precision, and after implantation, the device can move over time. Accurate knowledge of the IMD's position enables better interpretation of data sensed by the device and may allow wireless power to be focused on the IMD, thereby increasing power transfer efficiency and enabling greater implant depth. Existing positioning methods require device sizes and/or power consumption that exceed the limits of in vivo millimeter-sized IMD applications. We have previously proposed a novel implant positioning scheme by sensing the backscattered electromagnetic (EM) field to overcome those disadvantages, which is hence considered ideal for power- and area-constrained IMDs and suitable for wearable devices. This paper briefly reviews the previously proposed localization scheme and reports the progress of this research. Specifically, different approaches to realize this scheme are discussed and compared. Localization experiments in free space are then demonstrated, and the accuracy is shown on the order of millimeters. Different on-chip implementation procedures of measuring the backscattered EM field and their tradeoffs are described. Finally, conclusions and the future plan are presented.

TDOA-Based Source Localization With Distance-Dependent Noises

This paper focuses on the problem of source localization using time-difference-of-arrival (TDOA) measurements in both 2-D and 3-D spaces. Different from existing studies where the variance of TDOA measurement noises is assumed to be independent of the associated source-to-sensor distances, we consider the more realistic model where the variance is a function of the source-to-sensor distances, which dramatically complicates TDOA-based source localization. After formulating the distance-dependent noise model, we prove that using the extra information about the source location in the functional variance improves the estimation accuracy of TDOA-based source localization, but contributes little under a sufficiently small noise level. Further, we theoretically analyze the problem of optimal sensor placement, and derive the necessary and sufficient conditions for optimizing localization performance under different circumstances. Then, a localization scheme based on the iteratively reweighted generalized least squares (IRGLS) method is proposed to efficiently exploit the extra source location information. Finally, a simulation analysis confirms our theoretical studies, and shows that the performance of the proposed localization scheme is comparable to the Cramer-Rao lower bound (CRLB) given moderate TDOA measurement noises.

Distributed Wireless Sensor Network Localization Algorithm using Space Standard Normal Vector (SSNV)

—In this paper a low cost but effective localization algorithm for wireless sensor networks (WSNs) is introduced. From the proposed scheme unknown nodes only have to listen to three anchor nodes and establish a space standard normal vector (SSNV) to estimate the coordinates of them. Many localization algorithms for WSNs require the exits of extra components, such as a GPS, ultrasonic transceiver, and unidirectional antenna on sensor nodes. Conversely the proposed localization scheme is range-free which means there is no demanding of any extra devices for the sensors. In this scheme, by collecting information from the three nearest anchors a geometric plane surface is built whose standard normal vector is also obtained correspondingly. The estimated location of each unknown sensor is adjusted according to its relative normal vector in the space which belongs to the built plane surface. This paper compares the proposed scheme with the well-known DV-Hop mechanism, Centroid method and the OSSDL algorithm that we proposed before. Simulation results show that the proposed scheme outperforms the other three in localization accuracy, communication cost, and computational complexity. Analysis about the effects of different length of normal vector is also made.

Virtual Reference Device-Based NLOS Localization in Multipath Environment

This letter presents a novel non-line-of-sight (NLOS) localization scheme based on the concept of virtual reference device. The position of virtual reference device for each NLOS path can be determined if the initial mobile device position can be estimated or when the mobile device transits from LOS to NLOS region. With the position of virtual reference devices, the subsequent localization of mobile device requires only one signal path. Simulation and experiment conducted in indoor multipath environment show that the performance of our proposed localization scheme surpasses the existing localization schemes by a significant margin at all simulated and measured locations.

A Low-Cost Anchor Placement Strategy for Range-Free Localization Problems in Wireless Sensor Networks

The deployment of anchor nodes (or beacon nodes) is a key element in the design of range-free localization schemes for wireless sensor networks (WSNs). The majority of range-free localization schemes deploy numerous anchor nodes within the monitored region. However, in certain cases (e.g., hazardous areas), it may not be possible to manually install anchor nodes within the monitored region of a WSN. In this study, very few anchor nodes are installed at the boundary of a WSN monitored region to estimate the locations of unknown sensors. The locations of the unknown sensors are estimated based on the minimum hop counts to the anchor nodes. The average hop distance is estimated by applying parameters derived from prior experiments. The simulation results show that the range error of the proposed localization scheme can be as low as 0.15. The localization accuracy, computation cost, and communication cost of the proposed scheme are compared with those of the well-known DV-Hop method.

High precision localization for profiled extended object based on GHT

A high precision localization scheme for profiled extended objects based-on Generalized Hough Transform (GHT) is proposed. The proposed localization scheme utilizes the edge points’ gratitude orientations of profiled extended objects to build an R-table in frame t-1. When frame t is coming, we search the R-table according to the pre-computed edge points’ gratitude orientations of profiled extended objects in current frame, generating an accumulator array. The coordination corresponding to the accumulator's peak value is regarded as coarse localization point in current frame. Then, a relaxation iteration method is proposed to refine the coarse localization point to obtain a sub-pixel localization point. Numerical experiments show that the localization scheme has following characteristics: high-precision and stability. Furthermore, we present the results of our work which involves investigation of the performance evaluation for the proposed localization scheme.

3-D Localization Method for a Magnetically Actuated Soft Capsule Endoscope and Its Applications.

In this paper, we present a 3-D localization method for a magnetically actuated soft capsule endoscope (MASCE). The proposed localization scheme consists of three steps. First, MASCE is oriented to be coaxially aligned with an external permanent magnet (EPM). Second, MASCE is axially contracted by the enhanced magnetic attraction of the approaching EPM. Third, MASCE recovers its initial shape by the retracting EPM as the magnetic attraction weakens. The combination of the estimated direction in the coaxial alignment step and the estimated distance in the shape deformation (recovery) step provides the position of MASCE in 3-D. It is experimentally shown that the proposed localization method could provide 2.0-3.7 mm of distance error in 3-D. This study also introduces two new applications of the proposed localization method. First, based on the trace of contact points between the MASCE and the surface of the stomach, the 3-D geometrical model of a synthetic stomach was reconstructed. Next, the relative tissue compliance at each local contact point in the stomach was characterized by measuring the local tissue deformation at each point due to the preloading force. Finally, the characterized relative tissue compliance parameter was mapped onto the geometrical model of the stomach toward future use in disease diagnosis.

DuRT: Dual RSSI Trend Based Localization for Wireless Sensor Networks

Localization is a key issue in wireless sensor networks. The geographical location of sensors is important information that is required in sensor network operations such as target detection, monitoring, and rescue. These methods are classified into two categories, namely range-based and range-free. Range-based localizations achieve high location accuracy by using specific hardware or using absolute received signal strength indicator (RSSI) values, whereas range-free approaches obtain location estimates with lower accuracy. Because of the hardware and energy constraints in sensor networks, RSSI offers a convenient method to find the position of sensor nodes. However, in the presence of channel noise, fading, and attenuation, it is not possible to estimate the actual location. In this paper, we propose an RSSI-based localization scheme that considers the trend of RSSI values obtained from beacons to estimate the position of sensor nodes. Through applying polynomial modeling on the relationship between received RSSI and distance, we are able to locate the maximum RSSI point on the anchor trajectory. Using two such trajectories, the sensor position can be determined by calculating the intersection point of perpendiculars passing through the maximum RSSI point on each trajectory. In addition, we devised schemes to improve the localization method to perform under a variety of cases such as single trajectory, unavailability of RSSI trends, and so. The advantage of our scheme is that it does not rely on absolute RSSI values and hence, can be applied in dynamic environments. In simulations, we demonstrate that the proposed localization scheme achieves higher location accuracy compared with existing localization approaches.

Constraint-based Correspondence Matching for Stereo-based Interactive Robotic Massage Machine

Locating the 3D positions of the points on the human back is an essential issue in stereo-based interactive robotic back massage machines. In stereoscopic 3D localization, the 3D positions are determined from the corresponding image points captured by calibrated stereo cameras. However, detecting these corresponding points on the human back is highly challenging due to the smooth and texture-less characteristics of human skin. In the present study, this problem is resolved by means of a novel correspondences detection scheme designated as Correspondences from Epipolar geometry and Contours via Triangle barycentric coordinates (CECT). In the proposed approach, reliable correspondences are extracted from the edge contours of the human back by applying epipolar geometry, and these correspondences are then used to compute the correspondences of the featureless points within the edge contour using a triangle barycentric coordinate approach. The accuracy and robustness of the estimated correspondences are ensured by applying three geometric constraints, namely a similarity constraint, a shape constraint and an epipolar constraint. The performance of the proposed approach is demonstrated by means of a series of experiments involving 28 subjects and four different testing conditions. In addition, the accuracy of the proposed localization scheme is evaluated by comparing the estimated 3D positions with those obtained using the cun-based measurement method in Traditional Chinese Medicine (TCM).

A robust extended [formula omitted] filtering approach to multi-robot cooperative localization in dynamic indoor environments

Multi-robot cooperative localization serves as an essential task for a team of mobile robots to work within an unknown environment. Based on the real-time laser scanning data interaction, a robust approach is proposed to obtain optimal multi-robot relative observations using the Metric-based Iterative Closest Point (MbICP) algorithm, which makes it possible to utilize the surrounding environment information directly instead of placing a localization-mark on the robots. To meet the demand of dealing with the inherent non-linearities existing in the multi-robot kinematic models and the relative observations, a robust extended H∞ filtering (REHF) approach is developed for the multi-robot cooperative localization system, which could handle non-Gaussian process and measurement noises with respect to robot navigation in unknown dynamic scenes. Compared with the conventional multi-robot localization system using extended Kalman filtering (EKF) approach, the proposed filtering algorithm is capable of providing superior performance in a dynamic indoor environment with outlier disturbances. Both numerical experiments and experiments conducted for the Pioneer3-DX robots show that the proposed localization scheme is effective in improving both the accuracy and reliability of the performance within a complex environment.

A WSN-Based Localization Scheme Considering the Reliability of RSSI Measurements

In this paper, we propose a localization scheme considering the reliability of RSSI (Received Signal Strength Indication) measurements in the WSN (Wireless Sensor Network) environment. This scheme attempts to reduce location errors due to indoor obstacles or environmental factors, when location calculations are based on RSSI. The standard deviation is used to evaluate the reliability of RSSI measurements from the reference node. Also, the directional path loss exponent is calculated through learning with respect to the reference node. The experimental results show that the proposed localization scheme improves the performance significantly in terms of location accuracy, compared to the existing RSSI-based approaches.

Range-Free Localization Scheme in Wireless Sensor Networks Based on Bilateration

A low-cost yet effective localization scheme for wireless sensor networks (WSNs) is presented in this study. The proposed scheme uses only two anchor nodes and uses bilateration to estimate the coordinates of unknown nodes. Many localization algorithms for WSNs require the installation of extra components, such as a GPS, ultrasonic transceiver, and unidirectional antenna, to sensors. The proposed localization scheme is range-free (i.e., not demanding any extra devices for the sensors). In this scheme, two anchor nodes are installed at the bottom-left corner (Sink X) and the bottom-right corner (Sink Y) of a square monitored region of the WSN. Sensors are identified with the same minimum hop counts pair to Sink X and Sink Y to form a zone, and the estimated location of each unknown sensor is adjusted according to its relative position in the zone. This study compares the proposed scheme with the well-known DV-Hop method. Simulation results show that the proposed scheme outperforms the DV-Hop method in localization accuracy, communication cost, and computational complexity.

Strategic placement of localization devices (such as pilot points and anchors) in inverse modeling schemes

Localization schemes using devices such as pilot points or anchors (localization devices) are used in inversion schemes as a tool for gleaning information from measurements that can be used to constrain inversion schemes with the added benefit in the form of a potential for reduction in the number of parameters employed in the inversion scheme. This paper proposes and demonstrates a method for strategic placement of the localization devices. The method combines stochastic singular value decomposition with parameter rejection methods to produce a map of “intensity” scores which allows the inverse modeler to place the localization devices at locations defined by their probability for producing informative, probabilistic constraints on the statistical distributions of the target variables. We also show that the method can be used for selecting measurement locations when designing data acquisition campaigns. The method is demonstrated for the case of steady state flow in a heterogeneous conductivity field using MAD (method of anchored distributions). In summary, the proposed localization scheme intends to increase the information gleaned from measurements while reducing the associated computational costs associated with stochastic inversion.

A Localization Scheme for Wireless Sensor Networks Using Mobile Anchors With Directional Antennas

This paper proposes a range-free localization scheme for wireless sensor networks (WSNs) using mobile anchor nodes equipped with four directional antennas. In the proposed approach, each mobile anchor node determines its position via GPS, and then broadcasts its coordinates as it moves through the WSN. The sensor nodes detect these beacon messages and utilize a simple processing scheme to determine their own coordinates based on those of the anchors. The proposed approach removes the requirement for specific ranging hardware on the sensor nodes, avoids the need for communications between the sensor nodes. Moreover, the scheme is robust toward the effects of variations in the transmission range of the anchor nodes and the presence of obstacles in the sensing environment. The performance of the proposed scheme is evaluated by conducting a series of simulations using the ns-2 network simulator. The results show that the proposed localization scheme achieves a reduced localization error and a lower energy consumption than existing range-free solutions based on mobile anchor nodes over a wide range of typical network conditions.

PEER-TO-PEER LOCALIZATION IN URBAN AND INDOOR ENVIRONMENTS

This paper presents a novel peer-to-peer or mobile- to-mobile localization scheme for general indoor and outdoor environments. In this scheme, two mobile nodes at arbitrary locations are able to locate each other without the need of Line-of-Sight (LOS) path between the two mobile device, and without the need for any reference devices such as GPS or land base beacons. Existing peer- to-peer localization techniques make use of Time of Arrival (TOA) and Angle of Arrival (AOA) of LOS and single bounce scattering paths to derive line of possible mobile device positions (LPMDs). The intersections of LPMDs are then used to estimate the unknown mobile device position | referred to as the Line Segment Intersection. However, in a heavy multipath environment with many multiple- bounce scattering paths, existing techniques require weighting factors and threshold values which are speciflcally chosen for that particular environment in order to select the LPMDs that correspond to LOS and single-bounce scattering paths for localization. Large localization error will occur if multiple-bounce scattering paths' LPMDs are mistakenly used for intersections. In addition, existing techniques also do not work well in a multipath environment with high level of TOA and AOA noises especially when the angles between LPMDs are small. The accuracy of the Line Segment Intersection also deteriorates as the distance traveled by multipath signals become comparable to each other. This renders the weighting and threshold values inefiective. This paper presents a novel Gaussian weighting process to remove the abovementioned limitations. The Gaussian weighting process also dramatically improves the accuracy of the localization. Experimental coupled with simulation results show that our proposed localization scheme outperforms existing Peer-to-peer localization technique by a signiflcant margin of up to 83% and 54%

Automatic edge-based localization of facial features from images with complex facial expressions

Automatic localization of facial features is an essential step for many systems of face recognition, facial expression classification and intelligent vision-based human–computer interfaces. In this paper, we present automatic edge-based method of locating regions of prominent facial features from up-right facial images. The proposed localization scheme was tested on several public databases of complex facial expressions. The method demonstrated high localization rates when localization accuracy was evaluated by both a conventional point error measure and a new rectangular error measure that takes into account the location of the feature in the image and the true feature size.