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In multiple-target tracking problem, data association technique plays an significant role. When targets move closely or crosswise, performances of conventional data association algorithms which use kinematic information only may be degraded. Actually, beside the kinematic information, sensors always can obtain feature information about the target, and incorporating the features into data association...
This paper presents a novel and an improved approach for estimating the position of a vehicle using vehicle-infrastructure cooperative localization. In our previous work we presented a Factor Graph based solution which added the topology (inter-vehicle distance) as a constraint while localizing the vehicle using data from sensors from both inside and outside the vehicle. This paper extends the work...
Autonomous vehicles operating in dynamic environments rely on precise localization. In this paper we present a novel approach for cooperative localization of vehicular systems and an infrastructure RADAR which is resilient against outliers generated from the RADAR. The problem of cooperative localization is represented as a factor graph, where interrelated topologies (including that of outliers) are...
The conventional multi-target tracking (MTT) algorithms usually suffer from computational intractability problem. The appearance of Iterative Joint Integrated Probabilistic Data Association (iJIPDA) filter solves this problem by providing a tradeoff between the tracking performance and computational cost for computational resource management of sensor systems. However, the iJIPDA filter essentially...
In this paper, we consider the fluctuating targets detection problem in a distributed multi-sensor network. A multi-sensor multi-frame track-before-detect (MS-MF-TBD) procedure is proposed to sufficiently make use of the target energy diversity in space and time dimensions (space-time diversity). Two MS-MF-TBD methods, the multi-sensor maximum likelihood-probabilistic data association (MS-ML-PDA)...
In this paper, we consider the source localization problem in which several microphones collaborate to locate an active sound source in a reverberant environment. Sound source localization (SSL) based on the Generalized Cross Correlation (GCC) function is widely studied for the past few decades. However, in a reverberant environment, the maximal peak of the GCC function does not necessarily correspond...
This paper investigates the passive localization of a mobile source based on time difference of arrival (TDOA) measurements when the sensor positions suffer from random uncertainties. In the formulation of the dynamic system, the nonlinear measurement function contains random parameters, so the classical high-degree cubature Kalman filtering (CKF) method is unrealizable. We develop an augmented high-degree...
A practical method for full-dimension attitude determination based on the combination of two-antenna global positioning system (GPS) and strapdown inertial navigation system (SINS) is presented. In view of the fact that two-antenna GPS can only provide two attitude angles using carrier phase difference measurements, not all of the SINS attitude errors can be directly corrected by the integrated navigation...
Assessing the fundamental performance limitations in Bayesian filtering can be carried out using the parametric Cramér-Rao bound (CRB). The parametric CRB puts a lower bound on mean square error (MSE) matrix conditioned on a specific state trajectory realization. In this work, we derive the parametric CRB for state-space models, where the measurement equation is modeled by a Gaussian process regression...
Multi-resolution grid computation is a technique used to speed up source localization with a Maximum Likelihood Estimation (MLE) algorithm. In the case where the source is located midway between grid points, the MLE algorithm may choose an incorrect location, causing following iterations of the search to close in on an area that does not contain the source. To address this issue, we propose a modification...
Emission source localization and sensor registration using received signal strength (RSS) measurements is investigated. Previous studies for RSS localization assume that the sensors receiving signals are bias free, which is not the case in practice. This issue is taken into consideration in this paper for the localization problem. To avoid non-convexity of the global optimization problem for the traditional...
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