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Multi-target tracking using Doppler-shift only measurements is a difficult problem due to the lack of local observability. Multiple Doppler sensors are required to estimate in time the velocity and position vectors of a single-target. The situation is more complicated in multi-target scenarios due to the measurement-to-track assignment problem and approximations usually required in multi-sensor algorithms...
Efficient sensor nodes organization is one of the most critical and challenging tasks in building practical wireless sensor networks (WSNs). Due to energy efficiency, clustering has been widely used in WSNs, where each cluster head (CH) is a manager to control its members and collect sensed data from them. Currently, various CH selection techniques have been proposed. However, less emphasis was placed...
Emerging Camera Sensor Networks (CSN) leverage the collaboration, processing and communication capabilities of modern cameras to handle a wide variety of security and safety-critical tasks, including target tracking. However, the performance of CSN in terms of tracking accuracy can be severely degraded when faults occur. Faults may be caused by unpredictable software errors (e.g., in the image processing,...
Moving targets in Synthetic Aperture Radar (SAR) data impose several challenges for SAR processing. In full-aperture SAR images, moving objects appear smeared and/or displaced. In previous studies, we showed that a combination of sub-aperture processing, feature extraction, unscented Kalman filtering and multi-target hypotheses can reliably detect and track moving objects. In this paper, we present...
This paper extends our previous results on cooperative target tracking of a moving ground vehicle using multiple unmanned aerial vehicles with constant 2D horizontal range to a time-varying horizontal range. An early-designed guidance law that orbits one UAV around the target is modified to handle time-varying horizontal range given by a prescribed reference. Cooperative target tracking is achieved...
We present a framework to search for and track a target within an urban environment by fusing data from an Unmanned Aerial Vehicle and Unattended Ground Sensors. The target and UAV are restricted to a road network modeled as a directed graph with the ground sensors deployed along selected edges. The UAV is equipped with an onboard camera capable of detecting the target, and it is guided by an information-theoretic...
In this paper, the authors presents a review on the performance analysis of Extended Kalman Filter for tracking the single and multiple targets using bearings only measurements. The Estimator predicts the track of the object by assuming the initial state and noise parameters. The tracking of both single and multiple targets (in this paper two targets are considered) using Extended Kalman Filter is...
The triggering criterion of passive sensors cueing and handoff radar is deeply analyzed, focusing on its trigger mechanisms. This paper first analyzes the cueing and handoff demand and designs the multi-sensor fusion tracking model based on the synergistic characteristics of passive and active sensors. Then the covariance control is adopted to form the triggering criterions between passive sensors...
Local descriptors represent a powerful tool, which is exploited in several applications such as visual search, object recognition and visual tracking. Real-valued visual descriptors such as SIFT and SURF achieve state-of-the-art accuracy performance for a large set of visual analysis tasks. However, such algorithms are demanding in terms of computational capabilities and bandwidth, being unsuitable...
This paper presents a framework for information-theoretic based task assignment of multiple UAVs for searching and tracking moving targets. A stochastic approach which uses probability density functions is introduced as the information gathering metric. This algorithm yields trajectory that minimizes the uncertainty of unknown information. The presented task assignment is based on the negotiation...
Wireless sensor networks (WSNs) facilitate enormous applications in the field of habitat monitoring, disaster management, security, military, etc. Sensor Nodes are very tiny in size and that leads to limited processing power and battery capacity. Resource constrained nature of sensors makes them extremely vulnerable to failures. Moreover, mobility management is an important parameter that affects...
In this paper, an approach for a collision avoidance system for small Unmanned Surface Vehicles (USV) is presented. These kind of USVs are typically used for measuring tasks and thus, the collision avoidance algorithm has to take the mission objective and information about obstacles and other vessels into account. It generates an evasive trajectory that either leads around the obstacle, reduces the...
Radio tomographic imaging (RTI) is a promising technique which allows localizing and tracking targets carrying no electronic devices. It utilizes the attenuation of wireless links to generate images of the change in the propagation field. Objects that obstruct the wireless signals in the field will lead to bright blobs in RTI image. For multi-target tracking, we employ clustering to obtain cluster...
We address multiple object tracking in a system that has feedback from the fusion center to a wireless sensor network, where nodes transmit to the fusion center using random access. The feedback is used to adapt the sensing rate and, assuming that the sensors can move, to modify their positions. The variation in the position and the sensing rate of the sensors has the goal of providing higher accuracy...
Central catadioptric omnidirectional images exhibit serious nonlinear distortions due to quadratic mirrors involved. Conventional visual features developed based on the perspective model are hard to achieve a satisfactory performance when directly applied to the distorted omnidirectional image. This paper presents a parameterized neighborhood model to efficiently calculate the adaptive neighborhood...
During the last decade, detection, localization and tracking of moving persons by using UWB radars have attracted attention of researchers and final users as well. The problem of UWB sensors usage for these applications consists in the fact, that a single sensor is not very often able to localize a target situated in complex environment with the required reliability and accuracy. Therefore, UWB sensor...
Border surveillance requires regular patrolling to prevent intruders from crossing across, emphasizing the need for an automated network of sensing devices that is capable of detecting and estimating multiple moving targets. This paper proposes a fusion-driven decentralized sensor scheduling scheme that enables dynamic space-time clustering around multiple moving targets for energy-efficient track...
The constraint sufficient statistics distributed particle filter is a novel and effective solution for bearings-only single target tracking. The algorithm achieves a significant reduction in communication overhead by factorizing the likelihood function without suffering a major decrease in accuracy. However, the algorithm has some limitations which we discuss and explore in this paper. In particular,...
This paper presents a new image based hybrid algorithm for the maneuvering target tracking problem. An optimal filter for the mode of the target that fully exploits the imaging capacity of electro-optical sensors (EO) is introduced first. The second part presents the architecture of the hybrid imaging filter (HIF). The efficiency of the HIF leads to a significant improvement of the tracking performance...
We apply a variational approximation for multiple-target localization, and propose Variational Approximation Data Association Filter(VADAF) method, which minimize KL divergence between marginalized likelihood and approximated one. For multiple-target localization, we have to solve data association problem. The data association problem is that we can not associate data and targets deterministically,...
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