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This paper proposes a novel joint probabilistic data association (JPDA) filter for joint target tracking and track maintenance in the presence of unknown detection probability and clutter rate. The proposed algorithm consists of two main parts: (1) the standard JPDA filter with a Poisson point process birth model for multi-object state estimation; and (2) a multi-Bernoulli filter for detection probability...
The paper presents an approach for tracking a variable number of objects by using a multi-layer particle filter combined with an extended Expectation Maximization (EM) clustering. The approach works on basis of binary foreground images coming from previous background subtraction. The multi-layer particle filter is an improvement of a conventional particle filter approach. It uses an introduced adaptive...
We consider tracking of a target with elliptical nonlinear constraints on its motion dynamics. The state estimates are generated by sensors and sent over long-haul links to a remote fusion center for fusion. We show that the constraints can be projected onto the known ellipse and hence incorporated into the estimation and fusion process. In particular, two methods based on (i) direct connection to...
A tracking simulator is an online simulation system that achieves a permanent state synchronization with the targeted process by dynamically calibrating the model state after comparing process measurements with model results. Tracking simulators are a powerful industrial application that can be utilized as a plant-wide virtual sensor for process monitoring and diagnosis as well as a predictive tool...
Forty years of cross-disciplinary academic and industrial research & development work on radar tracking systems is surveyed, starting from the former implementations based on the α — β, the Kalman filter up to the modern implementations based on random set filters.
The paper addresses a fast implementation algorithm about distributed fusion with CPHD filter. An implementation method of distributed fusion based on maximum probability association (MPA), called MPA-DF, is presented. Though the performance of MPA-DF is a little worse than traditional Generalization Covariance Intersection (GCI) distributed fusion method, called GCI-DF, the former needs lower computational...
This paper presents an extended BLUE filter with Pitot tube and windspeed measurements. Though widely used in aviation, Pitot tube is ignored by scholars because it only measures the speed of an aircraft relative to the air. Investigation shows the linear combination of Pitot tube and windspeed measurements can yield aircraft velocity estimation to improve performance. After a thorough analysis of...
Although the existing correlation filter based on trackers has appeared to be more excellent in the visual tracking problem, there is still tremendous space for the improvement of the tracking performance, especially in the occlusion situation which is often ignored due to the difficulty in detection and processing. In this paper, a scale-adaptive tracker is proposed to handle the case of occlusion...
We have developed an innovative medical round robot “Terapio” in hospitals. This novel robot is mainly tasked to deliver medical armamentarium and manage round data. An implemented omni-directional mobile mechanism and a person tracking control system to follow a medical doctor realize smooth transferring movement from a nurse station to a patient's bedroom. In this paper, person tracking control...
Human-Following robots are being actively researched for their immense potential to carry out mundane tasks like load carrying and monitoring of target individual through interaction and collaboration. The recent advancements in vision and sensor technologies have helped in creating more user-friendly robots that are able to coexist with humans by leveraging the sensors for human detection, human...
The novel adaptive multiple-model target tracking algorithm presented here employs a non-asymptotic state and parameter estimator whose design hinges on a non-standard integral system representation. The same estimator can be used for target maneuver detection and isolation and hence constitutes the principal ingredient of the tracking algorithm. The algorithm does not maintain a model bank, but creates...
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...
In this paper, the task of Mission 7 of International Aerial Robotics Competition (IARC) is investigated. The quadrotor is required to autonomously navigate in a GPS-denied environment, and accomplish physical interaction with ground moving targets. In order to estimate the position of the quadrotor, a multi-sensor-compensation based method is designed and individual measurement errors are compensated...
This paper presents a kind of self-tuning filter in the colored noise environment when the noise variance is unknown. The main method of this filter is whitening the colored noise, and the correlation function is used to get the estimations of the variance of the noise. An example for the target tracking system is presented to design the self-tuning filter for the position and velocity, the simulating...
The paper is concerned with the target tracking in range-only wireless sensor networks (WSNs). To integrate the separated measurements from the WSN, a sequential fusion estimation method is presented in the sense of linear minimum mean squared error (LMMSE). Moreover, the un-scented transformation is used to implement the recursion of means and covariances, and this kind estimator is termed as sequential...
In this paper, we consider a scenario where sensors are deployed over a large geographical area for tracking a target with circular nonlinear constraints on its motion dynamics. The sensor state estimates are sent over long-haul networks to a remote fusion center for fusion. We are interested in different ways to incorporate the constraints into the estimation and fusion process in the presence of...
In this paper, a new centralized algorithm is developed to estimate the registration error and target states jointly based on the generalized labeled multi-Bernoulli (GLMB) filter. The bias pseudo-measurements are calculated with the tracks generated by the GLMB filter. Then, the bias estimates are computed to compensate the measurements for multi-target tracking. Since the estimates of the sensor...
In real world multiple extended target tracking problems, the presence of merged measurements is a frequently occurring phenomenon, however, most existing tracking algorithms in the literature assume that each target generates independent measurements. When this measurement merging phenomenon occurs, it increases the computational complexity of the tracking algorithms. Recently, the conditional joint...
Conventional point object model based automotive radar tracking system assumes at most one detection received from the target object at a time. However, in real applications for an extended object, such as a passenger car, located within a close range to a high-resolution radar or LIDAR, the system usually receives multiple reflections from different parts of the object. This can introduce large bias...
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...
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