Traffic Surveillance System Based on a High-Resolution Radar

Muñoz‐Ferreras, José‐María; Pérez-Martínez, F.; Calvo-Gallego, Jaime; López, A.; Dorta-Naranjo, B. Pablo; Blanco-del-Campo, A.

doi:10.1109/tgrs.2008.916465

Cited by 52 publications

(29 citation statements)

References 16 publications

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“…Long time thermal infrared (TIR) cameras are used for traffic monitoring due to their 'day-and-night' capability and their potential to derive temperature and temperature differences of objects [5], [6], [7]. Traffic surveillance is also an important civilian application of radars [8], which have the advantage of jointly providing the location and speed of the vehicles. Efficient radar based solutions have been proposed for monitoring non-urban roads or highways [9], [10] from remote sensing platforms, or city centers from terrestrial installations [8].…”

Section: A Sensing Technologiesmentioning

confidence: 99%

“…Traffic surveillance is also an important civilian application of radars [8], which have the advantage of jointly providing the location and speed of the vehicles. Efficient radar based solutions have been proposed for monitoring non-urban roads or highways [9], [10] from remote sensing platforms, or city centers from terrestrial installations [8]. SAR images can also be used to detect stationary vehicles [11].…”

Section: A Sensing Technologiesmentioning

confidence: 99%

See 1 more Smart Citation

Extraction of Vehicle Groups in Airborne Lidar Point Clouds With Two-Level Point Processes

Börcs

Benedek

2015

IEEE Trans. Geosci. Remote Sensing

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Section: A Sensing Technologiesmentioning

confidence: 99%

Section: A Sensing Technologiesmentioning

confidence: 99%

Extraction of Vehicle Groups in Airborne Lidar Point Clouds With Two-Level Point Processes

Börcs

Benedek

2015

IEEE Trans. Geosci. Remote Sensing

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“…To improve the reliablity and to extend the awareness range of the ego-perception, supporting infrastructure based systems have been suggested, e.g. based on dedicated radar sensors [2] or cameras [3]. For an appropriate deployment of such systems, several sensors would have to be mounted to sufficiently sense only a limited area like an urban intersection, which results in high deployment and maintenance costs.…”

Section: Introductionmentioning

confidence: 99%

Localization of Discrete Mobile Scatterers in Vehicular Environments Using Delay Estimates

Schmidhammer

Gentner

Siebler

2019

2019 International Conference on Localization and GNSS (ICL-GNSS)

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This paper presents a localization approach which aims to detect and localize discrete mobile scatterers. Therefore, a network of spatially distributed transmitting and receiving nodes is used. The localization problem is formulated as a non-linear optimization problem and corresponding performance bounds for the positioning error are provided. To solve the optimization problem, an iterative non-linear least squares approach is used, following the algorithm of Levenberg and Marquard. The proposed localization approach is evaluated based on wideband measurement data. It is shown, that the localization of mobile scatterers can be achieved. A further evaluation reveals a strong dependence of the localization performance on the preceding link level parameter estimation. Particularly sparse networks are shown to be sensitive to rich multipath environments.

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“…Popular approaches for vehicle tracking itself are often based on vision systems [7]- [10], radar [11], or a combination of such techniques [12]. Recently, solutions that employ low-cost, low-complexity sensors such as microphones [10], [13], magnetometers [14], [15], or accelerometers [16] have emerged.…”

Section: Introductionmentioning

confidence: 99%

Vehicle Tracking Based on Fusion of Magnetometer and Accelerometer Sensor Measurements With Particle Filtering

Hostettler

Djurić

2015

IEEE Trans. Veh. Technol.

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This is a post-print of a paper published in IEEE Transactions on Vehicular Technology. When citing this work, you must always cite the original article:R. Hostettler and P. M. Djurić, "Vehicle tracking based on fusion of magnetometer and accelerometer sensor measurements with particle filtering," Vehicular Technology, IEEE Transactions on, vol. 64,no. 11, Abstract-In this article, we propose a method for vehicle tracking on roadways using measurements of magnetometers and accelerometers. The measurements are used to build a low-cost, low-complexity vehicle tracking sensor platform for highway traffic monitoring. First, the problem is formulated by introducing the process model for the motion of the vehicle on the road and two measurement models, one for each of the sensors. Second, it is shown how the measurements of the sensors can be fused using particle filtering. The standard sampling importance resampling (SIR) particle filter is extended for processing of multi-rate sensor measurements and models that employ unknown static parameters. The latter are treated by Rao-Blackwellization. The performance of the method is demonstrated by computer simulations. It is found that it is feasible to fuse the two sensors for vehicle tracking and that the proposed multi-rate particle filter performs better than particle filters that process only measurements of one of the sensors. The main contribution of this paper is the novel approach of fusing the measurements of road-mounted magnetometers and accelerometers for vehicle tracking and traffic monitoring.

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Traffic Surveillance System Based on a High-Resolution Radar

Cited by 52 publications

References 16 publications

Extraction of Vehicle Groups in Airborne Lidar Point Clouds With Two-Level Point Processes

Extraction of Vehicle Groups in Airborne Lidar Point Clouds With Two-Level Point Processes

Localization of Discrete Mobile Scatterers in Vehicular Environments Using Delay Estimates

Vehicle Tracking Based on Fusion of Magnetometer and Accelerometer Sensor Measurements With Particle Filtering

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