			Home About us Contact

Target Tracking (target + tracking)

Distribution by Scientific Domains

Engineering	100%

Selected Abstracts

An adaptive joining mechanism for improving the connection ratio of ZigBee wireless sensor networks

INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS, Issue 2 2010
Tien-Wen Sung
Abstract Wireless sensor networks (WSNs) are well suited to many applications, including environment surveillance and target tracking. ZigBee is an IEEE 802.15.4-based standard that is considered suitable for WSNs. The functional operations of a ZigBee network rely on self-organized network connections and the proper deployment of sensor devices. However, the devices comprising a ZigBee network may become isolated from the network after the joining phase due to the configuration constraints of the ZigBee standard. This means that some deployed devices cannot join the network even though they can communicate with other joined nodes. These isolated devices reduce the efficiency of network operation and increase deployment costs. This paper proposes a ZigBee-compatible adaptive joining mechanism with connection shifting schemes to improve the connectivity of ZigBee networks, allowing them to operate at the expected efficiency. Simulation results show that the proposed mechanism significantly improves the join ratio of deployed sensor devices in ZigBee WSNs. Copyright © 2009 John Wiley & Sons, Ltd. [source]

On-line estimation and path planning for multiple vehicles in an uncertain environment

INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 8 2004
Jarurat Ousingsawat
Abstract A unified approach to cooperative target tracking and path planning for multiple vehicles is presented. All vehicles, friendly and adversarial, are assumed to be aircraft. Unlike the typical target tracking problem that uses the linear state and nonlinear output dynamics, a set of aircraft nonlinear dynamics is used in this work. Target state information is estimated in order to integrate into a path planning framework. The objective is to fly from a start point to a goal in a highly dynamic, uncertain environment with multiple friendly and adversarial vehicles, without collision. The estimation architecture proposed is consistent with most path planning methods. Here, the path planning approach is based on evolutionary computation technique which is then combined with a nonlinear extended set membership filter in order to demonstrate a unified approach. A cooperative estimation approach among friendly vehicles is shown to improve speed and routing of the path. Copyright © 2004 John Wiley & Sons, Ltd. [source]

Targeted driving using visual tracking on Mars: From research to flight

JOURNAL OF FIELD ROBOTICS (FORMERLY JOURNAL OF ROBOTIC SYSTEMS), Issue 3 2009
Won S. Kim
This paper presents the development, validation, and deployment of the visual target tracking capability onto the Mars Exploration Rover (MER) mission. Visual target tracking enables targeted driving, in which the rover approaches a designated target in a closed visual feedback loop, increasing the target position accuracy by an order of magnitude and resulting in fewer ground-in-the-loop cycles. As a result of an extensive validation, we developed a reliable normalized cross-correlation visual tracker. To enable tracking with the limited computational resources of a planetary rover, the tracker uses the vehicle motion estimation to scale and roll the template image, compensating for large image changes between rover steps. The validation showed that a designated target can be reliably tracked within several pixels or a few centimeters of accuracy over a 10-m traverse using a rover step size of 10% of the target distance in any direction. It also showed that the target is not required to have conspicuous features and can be selected anywhere on natural rock surfaces excluding rock boundary and shadowed regions. The tracker was successfully executed on the Opportunity rover near Victoria Crater on four distinct runs, including a single-sol instrument placement. We present the flight experiment data of the tracking performance and execution time. © 2009 Wiley Periodicals, Inc. [source]

Navigation Aided Image Processing in UAV Surveillance: Preliminary Results and Design of an Airborne Experimental System

JOURNAL OF FIELD ROBOTICS (FORMERLY JOURNAL OF ROBOTIC SYSTEMS), Issue 2 2004
Jonas Nygårds
This paper describes an airborne reconfigurable measurement system being developed at Swedish Defence Research Agency (FOI), Sensor Technology, Sweden. An image processing oriented sensor management architecture for UAV (unmanned aerial vehicles) IR/EO-surveillance is presented. Some preliminary results of navigation aided image processing in UAV applications are demonstrated, such as SLAM (simultaneous localization and mapping), structure from motion and geolocation, target tracking, and detection of moving objects. The design goal of the measurement system is to emulate a UAV-mounted sensor gimbal using a stand-alone system. The minimal configuration of the system consists of a gyro-stabilized gimbal with IR and CCD sensors and an integrated high-performance navigation system. The navigation system combines dGPS real-time kinematics (RTK) data with data from an inertial measurement unit (IMU) mounted with reference to the optical sensors. The gimbal is to be used as an experimental georeferenced sensor platform, using a choice of carriers, to produce military relevant image sequences for studies of image processing and sensor control on moving surveillance and reconnaissance platforms. Furthermore, a high resolution synthetic environment, developed for sensor simulations in the visual and infrared wavelengths, is presented. © 2004 Wiley Periodicals, Inc. [source]

Multi-sensor track-to-track fusion via linear minimum variance sense estimators

ASIAN JOURNAL OF CONTROL, Issue 3 2008
Li-Wei Fong
Abstract An integrated approach that consists of sensor-based filtering algorithms, local processors, and a global processor is employed to describe the distributed fusion problem when several sensors execute surveillance over a certain area. For the sensor tracking systems, each filtering algorithm utilized in the reference Cartesian coordinate system is presented for target tracking, with the radar measuring range, bearing, and elevation angle in the spherical coordinate system (SCS). For the local processors, each track-to-track fusion algorithm is used to merge two tracks representing the same target. The number of 2-combinations of a set with N distinct sensors is considered for central track fusion. For the global processor, the data fusion algorithms, simplified maximum likelihood (SML) estimator and covariance matching method (CMM), based on linear minimum variance (LMV) estimation fusion theory, are developed for use in a centralized track-to-track fusion situation. The resulting global fusers can be implemented in a parallel structure to facilitate estimation fusion calculation. Simulation results show that the proposed SML estimator has a more robust capability of improving tracking accuracy than the CMM and the LMV estimators. Copyright © 2008 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society [source]