The Experts below are selected from a list of 819 Experts worldwide ranked by ideXlab platform
Shunsuke Kamijo - One of the best experts on this subject based on the ideXlab platform.
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3d building model based pedestrian positioning method using gps glonass qzss and its reliability calculation
Gps Solutions, 2016Co-Authors: Yanlei Gu, Shunsuke KamijoAbstract:The current low-cost global navigation satellite systems (GNSS) receiver cannot calculate satisfactory positioning results for pedestrian applications in urban areas with dense buildings due to multipath and non-line-of-sight effects. We develop a rectified positioning method using a basic three-dimensional city building model and ray-tracing simulation to mitigate the signal reflection effects. This proposed method is achieved by implementing a particle filter to distribute possible position candidates. The likelihood of each candidate is evaluated based on the similarity between the pseudorange measurement and simulated pseudorange of the candidate. Finally, the expectation of all the candidates is the rectified positioning of the proposed map method. The proposed method will serve as one sensor of an integrated system in the future. For this purpose, we successfully define a positioning accuracy based on the distribution of the candidates and their pseudorange similarity. The real data are recorded at an urban canyon environment in the Chiyoda district of Tokyo using a commercial grade u-blox GNSS receiver. Both static and dynamic tests were performed. With the aid of GLONASS and QZSS, it is shown that the proposed method can achieve a 4.4-m 1ź positioning error in the tested urban canyon area.
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nlos correction exclusion for gnss measurement using raim and city building models
Sensors, 2015Co-Authors: Li-ta Hsu, Shunsuke KamijoAbstract:Currently, global navigation satellite system (GNSS) receivers can provide accurate and reliable positioning service in open-field areas. However, their performance in the downtown areas of cities is still affected by the multipath and none-line-of-sight (NLOS) receptions. This paper proposes a new positioning method using 3D building models and the receiver autonomous integrity monitoring (RAIM) satellite selection method to achieve satisfactory positioning performance in urban area. The 3D building model uses a ray-tracing technique to simulate the line-of-sight (LOS) and NLOS signal travel distance, which is well-known as pseudorange, between the satellite and receiver. The proposed RAIM fault detection and exclusion (FDE) is able to compare the similarity between the raw pseudorange measurement and the simulated pseudorange. The measurement of the satellite will be excluded if the simulated and raw Pseudoranges are inconsistent. Because of the assumption of the single reflection in the ray-tracing technique, an inconsistent case indicates it is a double or multiple reflected NLOS signal. According to the experimental results, the RAIM satellite selection technique can reduce by about 8.4% and 36.2% the positioning solutions with large errors (solutions estimated on the wrong side of the road) for the 3D building model method in the middle and deep urban canyon environment, respectively.
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GPS Error Correction With Pseudorange Evaluation Using Three-Dimensional Maps
IEEE Transactions on Intelligent Transportation Systems, 2015Co-Authors: Shunsuke Miura, Li-ta Hsu, Feiyu Chen, Shunsuke KamijoAbstract:The accuracy of the positions of a pedestrian is very important and useful information for the statistics, advertisement, and safety of different applications. Although the GPS chip in a smartphone is currently the most convenient device to obtain the positions, it still suffers from the effect of multipath and nonline-of-sight propagation in urban canyons. These reflections could greatly degrade the performance of a GPS receiver. This paper describes an approach to estimate a pedestrian position by the aid of a 3-D map and a ray-tracing method. The proposed approach first distributes the numbers of position candidates around a reference position. The weighting of the position candidates is evaluated based on the similarity between the simulated pseudorange and the observed pseudorange. Simulated Pseudoranges are calculated using a ray-tracing simulation and a 3-D map. Finally, the proposed method was verified through field experiments in an urban canyon in Tokyo. According to the results, the proposed approach successfully estimates the reflection and direct paths so that the estimate appears very close to the ground truth, whereas the result of a commercial GPS receiver is far from the ground truth. The results show that the proposed method has a smaller error distance than the conventional method.
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gps precise positioning with pseudorange evaluation using 3 dimensional maps
Intelligent Vehicles Symposium, 2014Co-Authors: Shunsuke Miura, Feiyu Chen, Shunsuke KamijoAbstract:The accurate and reliable positions of pedestrians are important and useful information. Although global positioning systems (GPSs) in smartphones are currently the most convenient devices to obtain the positions of pedestrians, GPSs still have problems with their accuracy and reliability because of the performance degradation caused by multipath and non-line-of-sight (NLOS) propagation in urban canyons. This study describes an approach to estimate a position by searching around the reference position. Position candidates are prepared and evaluated based on the similarity between the simulated pseudorange from the candidate and the observed pseudorange. Simulated Pseudoranges are calculated on the basis of a ray-tracing simulation. The proposed method was verified through field experiments in urban canyons in Tokyo. It successfully estimates the reflection paths and direct paths so that the estimate appears very close to the ground truth even though the GPS result is far away from the ground truth.
Zaher M Kassas - One of the best experts on this subject based on the ideXlab platform.
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lane level localization and mapping in gnss challenged environments by fusing lidar data and cellular Pseudoranges
IEEE Transactions on Intelligent Vehicles, 2019Co-Authors: Mahdi Maaref, Joe Khalife, Zaher M KassasAbstract:A method for achieving lane-level localization in global navigation satellite system (GNSS)-challenged environments is presented. The proposed method uses the Pseudoranges drawn from unknown ambient cellular towers as an exclusive aiding source for a vehicle-mounted light detection and ranging (lidar) sensor. The following scenario is considered. A vehicle aiding its lidar with GNSS signals enters an environment where these signals become unusable. The vehicle is equipped with a receiver capable of producing Pseudoranges to unknown cellular towers in its environment. These Pseudoranges are fused through an extended Kalman filter to aid the lidar odometry, while estimating the vehicle's own state (3-D position and orientation) simultaneously with the position of the cellular towers and the difference between the receiver's and cellular towers’ clock error states (bias and drift). The proposed method is computationally efficient and is demonstrated to achieve lane-level accuracy in different environments. Simulation and experimental results with the proposed method are presented illustrating a close match between the vehicle's true trajectory and estimated using the cellular-aided lidar odometry over a 1 km trajectory. The proposed method yielded a 68% reduction in the 2-D position root mean-squared error (RMSE) over lidar odometry-only.
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navigation with cellular cdma signals part i signal modeling and software defined receiver design
IEEE Transactions on Signal Processing, 2018Co-Authors: Joe Khalife, Kimia Shamaei, Zaher M KassasAbstract:A software-defined receiver (SDR) for navigation using cellular code-division multiple access (CDMA) signals is presented. The cellular forward link signal structure is described, and models for the transmitted and received signals are developed. Particular attention is paid to relevant information that could be extracted and subsequently exploited for positioning and timing purposes. The pseudorange from the proposed receiver is modeled and the pseudorange error is studied in an additive white Gaussian channel. Experimental results with aerial and ground vehicles utilizing the proposed SDR are presented demonstrating a close match between the variation in Pseudoranges and the variation in true ranges between the receiver and two cellular CDMA base transceiver stations (BTSs). Moreover, the dynamics of the discrepancy between the observed clock biases of different sectors of the same BTS cell is modeled and validated experimentally. The consistency of the obtained model is analyzed through experimental tests in different locations, at different times, and for different cellular providers.
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optimal collaborative mapping of terrestrial transmitters receiver placement and performance characterization
IEEE Transactions on Aerospace and Electronic Systems, 2018Co-Authors: Joshua J Morales, Zaher M KassasAbstract:Mapping multiple unknown terrestrial signals of opportunity (SOP) transmitters via multiple collaborating receivers is considered. The receivers are assumed to have knowledge about their own states, make pseudorange observations on multiple unknown SOPs, and fuse these Pseudoranges through a central estimator. Two problems are considered. The first problem assumes multiple receivers with random initial states to pre-exist in the environment. The question of where to optimally place an additional receiver so to maximize the quality of the estimate of the SOPs’ states is addressed. A novel, computationally efficient optimization criterion that is based on area-maximization is proposed. It is shown that the proposed optimization criterion yields a convex program, the solution of which is comparable to two classical criteria: minimization of the geometric dilution of precision (GDOP) and maximization of the determinant of the inverse of the GDOP matrix. The second problem addresses the optimal mapping performance as a function of time and number of receivers in the environment. It is demonstrated that such optimal performance assessment could be generated off-line without knowledge of the receivers’ trajectories or the receivers’ estimates of the SOP. Experimental results are presented demonstrating collaborative mapping of an unknown terrestrial SOP emanating from a cellular tower for various receiver trajectories versus the optimal mapping performance.
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pose estimation with lidar odometry and cellular Pseudoranges
IEEE Intelligent Vehicles Symposium, 2017Co-Authors: Joe Khalife, Sonya Ragothaman, Zaher M KassasAbstract:A pose estimation framework by fusing light detection and ranging (lidar) odometry measurements and cellular Pseudoranges using an extended Kalman filter is proposed. Iterative closest point (ICP) is used to solve for the relative pose between lidar scans. A maximum likelihood estimator is developed for lidar scan registration. The proposed framework works with few ICP iterations; hence, can be used for real-time applications. The framework is tested experimentally, and it is demonstrated that the two-dimensional position root mean square error obtained with ICP only can be reduced by 93.58% by fusing lidar odometry and cellular Pseudoranges.
Philippe Bonnifait - One of the best experts on this subject based on the ideXlab platform.
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set membership position estimation with gnss pseudorange error mitigation using lane boundary measurements
IEEE Transactions on Intelligent Transportation Systems, 2019Co-Authors: Luis Conde Bento, Philippe Bonnifait, Urbano NunesAbstract:Model-based positioning methods involve nonlinear equations as is the case when using satellite Pseudoranges on global navigation satellite systems (GNSSs) and local measurements on road features. As these are nonlinear models, classical estimation methods cannot provide guaranteed position estimation and can converge to local optima, sometimes far away from the global optimum or the true value. Based on interval analysis, set inversion, and constraints propagation on real values provide a framework that guarantees to find the true position with a characterized confidence domain. This paper describes an error bounded set membership algorithm that computes the absolute position of a road vehicle by using raw GNNS Pseudoranges, lane boundary measurements, and a 2D road network map as geometric constraints. The algorithm is based on set inversion using interval analysis, and bounds are set on the measurements by taking into account a chosen risk. The GNSS Pseudoranges errors are modeled carefully, and road constraints are formalized to provide additional information in the data fusion process. The proposed algorithm, named lane boundary augmented set-membership GNSS positioning (LB-ASGP), provides a novel and inexpensive approach to improve position estimation performance for road vehicles guaranteeing the enclosure of the computed solution with high confidence. Results from simulations and field experiments show that the LB-ASGP significantly reduces GNSS errors in the direction perpendicular to the lane thanks to the lane boundary measurements.
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Sequential Data Fusion of GNSS Pseudoranges and Dopplers With Map-Based Vision Systems
IEEE Transactions on Intelligent Vehicles, 2017Co-Authors: Zui Tao, Philippe BonnifaitAbstract:Tightly coupling GNSS pseudorange and Doppler measurements with other sensors is known to increase the accuracy and consistency of positioning information. Nowadays, high-accuracy geo-referenced lane marking maps are seen as key information sources in autonomous vehicle navigation. When an exteroceptive sensor such as a video camera or a lidar is used to detect them, lane markings provide positioning information which can be merged with GNSS data. In this paper, measurements from a forwards-looking video camera are merged with raw GNSS Pseudoranges and Dopplers on visible satellites. To create a localization system that provides pose estimates with high availability, dead reckoning sensors are also integrated. The data fusion problem is then formulated as sequential filtering. A reduced-order state space modeling of the observation problem is proposed to give a real-time system that is easy to implement. A Kalman filter with measured input and correlated noises is developed using a suitable error model of the GNSS Pseudoranges. Our experimental results show that this tightly coupled approach performs better, in terms of accuracy and consistency, than a loosely coupled method using GNSS fixes as inputs.
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cooperative localization of vehicles sharing gnss Pseudoranges corrections with no base station using set inversion
IEEE Intelligent Vehicles Symposium, 2016Co-Authors: Khaoula Lassoued, Philippe Bonnifait, Isabelle FantoniAbstract:Fully distributed localization methods with no central server are relevant for autonomous vehicles that need real-time cooperation. In this paper, mobile vehicles share estimates of GNSS Pseudoranges common errors also known as biases. The biases that affect the Pseudoranges are mainly due to signal propagation and inaccurate ephemeris data. By describing the measurements models as geometric constraints on intervals, cooperative localization turns into distributed set inversion problem. The solution of this problem is guaranteed to contain the true vehicles positions. We consider vehicles which cooperate and exchange information in order to improve the absolute and relative estimation by fusing Pseudoranges corrections shared between them. Results using real measurements are presented to illustrate the performance of the proposed approach in comparison with a standalone method.
Kai Liu - One of the best experts on this subject based on the ideXlab platform.
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improving positioning accuracy using gps pseudorange measurements for cooperative vehicular localization
IEEE Transactions on Vehicular Technology, 2014Co-Authors: Kai Liu, Hock Beng Lim, Emilio Frazzoli, Victor C S LeeAbstract:Accurate positioning is a key factor for enabling innovative applications in intelligent transportation systems. Cutting-edge communication technologies make cooperative localization a promising approach for accurate vehicle positioning. In this paper, we first propose a ranging technique called weighted least squares double difference (WLS-DD), which is used to detect intervehicle distances based on the sharing of GPS pseudorange measurements and a weighted least squares method. It takes the carrier-to-noise ratio (CNR) of raw pseudorange measurements into consideration for mitigating noises so that it can improve the accuracy of the distance detection. We show the superiority of WLS-DD by conducting a series of field experiments. Based on intervehicle distance detection, we propose a distributed location estimate algorithm (DLEA) to improve the accuracy of vehicle positioning. The implementation of DLEA only relies on inaccurate GPS pseudorange measurements and the obtained intervehicle distances without using any reference points for positioning correction. Moreover, to evaluate the joint effect of WLS-DD and DLEA, we derive a data fitting model based on the observed distance detection bias from field experiments, which generates parameters in a variety of environments for performance evaluation. Finally, we demonstrate the effectiveness of the proposed solutions via a comprehensive simulation study.
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a gps pseudorange based cooperative vehicular distance measurement technique
Vehicular Technology Conference, 2012Co-Authors: Daiqin Yang, Fang Zhao, Kai Liu, Hock Beng Lim, Emilio Frazzoli, Daniela RusAbstract:Accurate vehicular localization is important for various cooperative vehicle safety (CVS) applications such as collision avoidance, turning assistant, etc. In this paper, we propose a cooperative vehicular distance measurement technique based on the sharing of GPS pseudorange measurements and a weighted least squares method. The classic double difference pseudorange solution, which was originally designed for high-end survey level GPS systems, is adapted to low-end navigation level GPS receivers for its wide availability in ground vehicles. The Carrier to Noise Ratio (CNR) of raw pseudorange measurements are taken into account for noise mitigation. We present a Dedicated Short Range Communications (DSRC) based mechanism to implement the exchange of pseudorange information among neighboring vehicles. As demonstrated in field tests, our proposed technique increases the accuracy of the distance measurement significantly compared with the distance obtained from the GPS fixes.
Hock Beng Lim - One of the best experts on this subject based on the ideXlab platform.
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improving positioning accuracy using gps pseudorange measurements for cooperative vehicular localization
IEEE Transactions on Vehicular Technology, 2014Co-Authors: Kai Liu, Hock Beng Lim, Emilio Frazzoli, Victor C S LeeAbstract:Accurate positioning is a key factor for enabling innovative applications in intelligent transportation systems. Cutting-edge communication technologies make cooperative localization a promising approach for accurate vehicle positioning. In this paper, we first propose a ranging technique called weighted least squares double difference (WLS-DD), which is used to detect intervehicle distances based on the sharing of GPS pseudorange measurements and a weighted least squares method. It takes the carrier-to-noise ratio (CNR) of raw pseudorange measurements into consideration for mitigating noises so that it can improve the accuracy of the distance detection. We show the superiority of WLS-DD by conducting a series of field experiments. Based on intervehicle distance detection, we propose a distributed location estimate algorithm (DLEA) to improve the accuracy of vehicle positioning. The implementation of DLEA only relies on inaccurate GPS pseudorange measurements and the obtained intervehicle distances without using any reference points for positioning correction. Moreover, to evaluate the joint effect of WLS-DD and DLEA, we derive a data fitting model based on the observed distance detection bias from field experiments, which generates parameters in a variety of environments for performance evaluation. Finally, we demonstrate the effectiveness of the proposed solutions via a comprehensive simulation study.
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a gps pseudorange based cooperative vehicular distance measurement technique
Vehicular Technology Conference, 2012Co-Authors: Daiqin Yang, Fang Zhao, Kai Liu, Hock Beng Lim, Emilio Frazzoli, Daniela RusAbstract:Accurate vehicular localization is important for various cooperative vehicle safety (CVS) applications such as collision avoidance, turning assistant, etc. In this paper, we propose a cooperative vehicular distance measurement technique based on the sharing of GPS pseudorange measurements and a weighted least squares method. The classic double difference pseudorange solution, which was originally designed for high-end survey level GPS systems, is adapted to low-end navigation level GPS receivers for its wide availability in ground vehicles. The Carrier to Noise Ratio (CNR) of raw pseudorange measurements are taken into account for noise mitigation. We present a Dedicated Short Range Communications (DSRC) based mechanism to implement the exchange of pseudorange information among neighboring vehicles. As demonstrated in field tests, our proposed technique increases the accuracy of the distance measurement significantly compared with the distance obtained from the GPS fixes.
