Improved Target Tracking with Road Network Information

Orguner, Umut
Gustafsson, Fredrik
In this paper we consider the problem of tracking targets, which can move both on-road and off-road, with particle filters utilizing the road-network information. It is argued that the constraints like speed-limits and/or one-way roads generally incorporated into on-road motion models make it necessary to consider additional high-bandwidth off-road motion models. This is true even if the targets under consideration are only allowed to move on-road due to the possibility of imperfect road-map information and drivers violating the traffic rules. The particle filters currently used struggles during sharp mode transitions, with poor estimation quality as a result. This is due to the fact the number of particles allocated to each motion mode is varying according to the mode probabilities. A recently proposed interacting multiple model (IMM) particle filtering algorithm, which keeps the number of particles in each mode constant irrespective of the mode probabilities, is applied to this problem and its performance is compared to a previously existing algorithm. The results of the simulations on a challenging bearing-only tracking scenario show that the proposed algorithm, unlike the previously existing algorithm, can achieve good performance even under the sharpest mode transitions.


Performance Comparison of Target Tracking Algortihms in Underwater Environment
Ege, Emre; Saranlı, Afşar (2008-04-22)
Target tracking is one the most fundamental elements of a radar system. The aim of target tracking is the reliable estimation of a target's true state based on a time history of noisy sensor observations. In real life, the sensor data may include substantial noise. This noise can render the raw sensor data unsuitable to be used directly. Instead, we must filter the noise, preferably in an optimal manner. For land, air and surface marine vehicles, very successful filtering methods are developed. However, bec...
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Soyman, Yusuf (2012-04-24)
In this paper, a robust automatic target recognition algorithm in FLIR imagery is proposed. Target is first segmented out from the background using wavelet transform. Segmentation process is accomplished by parametric Gabor wavelet transformation. Invariant features that belong to the target, which is segmented out from the background, are then extracted via moments. Higher-order moments, while providing better quality for identifying the image, are more sensitive to noise. A trade-off study is then perform...
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Kumru, Murat; Özkan, Emre; Department of Electrical and Electronics Engineering (2022-9-09)
In this thesis, we consider the problem of tracking dynamic objects with unknown shapes using point cloud measurements generated by, e.g., lidars, radars, and depth cameras. The point measurements do not only convey information about the object pose, i.e., position and orientation, but they also naturally reveal the characteristics of its latent extent. Aiming to harness the full potential of the available information, we investigate the Gaussian process-based extended object tracking (GPEOT) framework. W...
Multi-target particle filter based track before detect algorithms for spawning targets /
Eyili, Mehmet; Demirekler, Mübeccel; Department of Electrical and Electronics Engineering (2014)
In this work, a Track Before Detect (TBD) approach is proposed for tracking and detection of the spawning targets on the basis of raw radar measurements. The principle of this approach is mainly constructed by multi-model particle filter method. In contrast to the related works in the literature, a novel reduced order dynamic model is introduced and the information about bearing angle derived from the radar measurements is not used in this model to improve the efficiency of the particle filter. Moreover, a ...
Enhancing GPS positioning accuracy from the generation of ground-truth reference points for on-road urban navigation
Bshara, Mussa; Orguner, Umut; Gustafsson, Fredrik; Van Biesen, Leo (2012-09-14)
The global positioning system (GPS) is a Global Navigation Satellite System (GNSS) uses a constellation of between 24 and 32 Medium Earth Orbit satellites that transmit precise microwave signals, which enable GPS receivers to determine their current location, the time, and their velocity [1]. Initially, the GPS was developed for military applications, but very quickly became the most used technology in positioning even for end-user applications run by individuals with no technical skills. GPS reading are us...
Citation Formats
U. Orguner and F. Gustafsson, “Improved Target Tracking with Road Network Information,” 2009, Accessed: 00, 2020. [Online]. Available: