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We present a method to model and classify trajectory data that come from surveillance videos. Observations of the locations of moving entities are used to estimate their expected velocity in the scene. Such estimation is performed by a Gaussian process regression that enables to approximate probabilistically the expected velocity of entities given some observed evidence in the scene. Subsequently,...
Correct knowledge of noise statistics is essential for an effective estimator in maneuvering target tracking. In practice, however, the noise statistics are usually unknown or not perfectly known. To deal with the estimation problem in linear discrete-time systems with Markov jump parameters, where the measurement noise covariance is unknown, a novel approach is presented in this paper. This approach...
We propose a novel joint tracking and mitigation scheme for linear dynamic impairments using a 3-stage extended Kalman filter. Simulation results show that it can quickly track and compensate the impairments including multi-polarization effects, frequency offset and phase noise.
In this paper, a multi-model dynamic fusion soft sensor modeling method based on Gauss-Markov estimation is proposed. Firstly, the fuzzy c-means algorithm is used to cluster the input samples of the model. The radial basis function and least square support vector machine are used to establish multiple sub-models for each clustering. The multi-model outputs are predicted by dynamic fusing the values...
The quantity and diversity of data in Light-Field videos makes this content valuable for many applications such as mixed and augmented reality or post-production in the movie industry. Some of such applications require a large parallax between the different views of the Light-Field, making the multi-view capture a better option than plenoptic cameras. In this paper we propose a dataset and a complete...
This paper deals with the scenario of two multi-UAV systems (so-called teams), each flying from a starting point to a target point. The teams meet on their ways and have to avoid collisions in the horizontal plane. Both teams work independent of each other but use the same formation-control and obstacle-collision-avoidance algorithm. The leaders measure obstacles' positions, use a Kalman Filter to...
This paper studies and formulates the problem of distributed filtering with a diffusion strategy for state estimation of a dynamic system by using observations from sensors in a network. The sensor-nodes have estimation ability and work in a collaborative manner. The information transmission across the network abides by the diffusion strategy that each node communicates only with its neighbors. First,...
The set-membership information fusion problem is investigated for general multisensor nonlinear dynamic systems. Compared with linear dynamic systems and point estimation fusion in mean squared error sense, it is a more challenging nonconvex optimization problem. Usually, to solve this problem, people try to find an efficient or heuristic fusion algorithm. It is no doubt that an analytical fusion...
This paper presents a compressed sensing based sensor selection algorithm for direction-of-arrival estimation, in a large scale randomly distributed sensor array. First, a target tracker is employed for the prior information of target position. Second, according to the prior information, we reduce rank of sensing matrix by narrowing the interesting area. Third, a linear independence combination of...
This paper investigates the box-particle filter for multi-target tracking, and proposes a clustering based box-particle implementation of PHD filter. A subdivision step is added before the estimation of states. Each box is divided into several sub-box based on the estimated number of targets. An equivalent set of particles can be extracted from the set of subdivided boxes. Then, clustering technique...
We present a method for developing executable algorithms for quantitative cyber-risk assessment. Exploiting techniques from security risk modeling and actuarial approaches, the method pragmatically combines use of available empirical data and expert judgments. The input to the algorithms are indicators providing information about the target of analysis, such as suspicious events observed in the network...
Distributed algorithms are proposed to solve distributed optimization problems for a network of strongly connected agents in this paper. The proposed algorithms are based on a combination of a leader-following consensus protocol and the gradient descent method/primal-dual dynamics. In the leader-following consensus protocol, each agent acts as a virtual leader that provides its local measurements...
The present paper discusses different techniques of measuring Carrier-to-Noise density ratio (C/N0) in navigation and information-communication systems. C/N0 means the ratio of the received signal power to the noise spectral density N0 at receiver's input (at the output of an antenna with a low-noise amplifier (LNA)). Correlation processing is performed in the receiver to obtain in-phase (I) and quadra-phase...
Many enterprises have a growing interest in service composition to construct their business applications. With the increase of alternative services, Quality of Service (QoS) becomes an important indicator of obtaining optimal composite services. Due to the dynamic nature of the service environment, a composite service may not guarantee to deliver an overall optimal QoS. Re-optimization approaches...
In this paper, non-linear estimators and feed-forward actions are designed to solve a vehicular platoon control problem. In particular, these estimators are useful in implementation of a Multi-Layer Consensus Seeking approach to the platooning problem. In the Multi-Layer approach the feed-forward part is built separately from the feedback part, based on desired trajectories. This opens the way to...
It is common to assume that there is only one degradation mechanism in the system in recent works on prognostics focusing on estimation of the remaining useful life (RUL) of an electromechanical system. However, there are cases in which the system may be subjected to more than one failure (degradation) mechanisms due to different stress factors, types of components and their interactions with one...
The highly limited number of observation results in the increase of the prediction errors. In such case the linear Kalman filter (KF) will work within the unsteady state, which can lead to unpredictable results. The paper presents an alternative, simplified methods for the tracked object position prediction with the linearization of the trajectory. The obtained results are compared with the KF predictions...
Crowdsourcing allows requesters to allocate tasks to a group of workers on the Internet to make use of their collective intelligence. Quality control is a key design objective in incentive mechanisms for crowdsourcing as requesters aim at obtaining answers of high quality under a given budget. However, when measuring workers' long-term quality, existing mechanisms either fail to utilize workers' historical...
This paper addresses distributed consensus problem for multi-agent systems with general linear time-invariant dynamics and undirected connected communication graphs. A distributed adaptive consensus protocol is found to solve problems of existing adaptive consensus protocols related to different, generally large and possibly unbounded coupling gains. This protocol guarantees ultimate boundedness under...
The Firefighter Problem (FFP) is an optimization problem of developing an optimal strategy for assigning firemen to nodes of a given graph in successive iterations of a simulation of spread of fires in the graph. This paper focusses on an extension of the original FFP, namely the Bi-Firefighter Problem (FFP2), where the second element (water) is introduced. FFP2 corresponds to the practical optimization...
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