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Asynchronous track-to-track fusion by direct estimation of time of sample in sensor networks
, Article IEEE Sensors Journal ; Vol. 14, issue. 1 , Jan , 2014 , p. 210-217 ; 1530437X ; Hemmatyar, A. M. A ; Sharif University of Technology
Abstract
Asynchronous data fusion is inevitable in track-to-track fusion for tracking high-speed targets. For low-speed targets, e.g., the movement of clouds, synchronization is insignificant and, depending on the application, may be disregarded. Real-time asynchronous fusion is a demanding task in sensor networks when the sensors are not synchronous in sampling-rate or in sampling-phase. In the method proposed in this paper, an estimator in the fusion center estimates the actual time of the sample with respect to the time-reference of the fusion center upon receiving the data from a sensor. Then, the computer of the fusion center uses predictions to transfer all the received data to the data...
Robust Vision-Based Pose and Parameter Estimation of Unknown Space Objects in the Cluttered Orbits
, Ph.D. Dissertation Sharif University of Technology ; Malaek, Mohammad Bagher (Supervisor)
Abstract
To provide a safe environment for space equipments and infrastructures in addition to managing the role of hazardous objects that are known as space debris, the presented thesis describes a new robust technique to estimate the dynamic states and inertial parameters of Uncooperative Space Objects (USO) with uncertain dynamics in the cluttered orbits. The prescribed method is especially effective to capture stray objects, capture and servicing of the satellites, rendezvous and collision avoidance maneuvers, space explorations as well as Actrive Debris Removal (ADR) missions. Such missions call for high degree of precision and reliable estimation methods. The proposed estimation architecture...
Practical method to predict an upper bound for minimum variance track-to-track fusion
, Article IET Signal Processing ; Volume 11, Issue 8 , 2017 , Pages 961-968 ; 17519675 (ISSN) ; Malaek, S. M. B ; Sharif University of Technology
Abstract
This study deals with the problem of track-to-track fusion in a sensor network when the correlation terms between the estimates of the agents are unknown. The proposed method offers an upper bound for the optimal minimum variance fusion rule through construction of the correlation terms according to an optimisation scheme. In general, the upper bound filter provides an estimate that is more conservative than the optimal estimate generated by the minimum variance fusion rule, while at the same time is less conservative than one obtained by the widely used covariance intersection method. From the geometrical viewpoint, the upper bound filter results in the inscribed largest volume ellipsoid...