The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In this paper, a joint revisit and dwell time management (JRDTM) strategy for single target tracking based on the predicted Bayesian Cramer-Rao lower bound (BCRLB) in phased array radar system is addressed. We achieve the time resources management by formulating and solving an optimization problem, which is to minimize the resource amount used for tracking with the tracking accuracy of the target...
In this paper, we will investigate a joint beam and dwell time allocation strategy for multiple targets tracking based on the phased array radar system. We achieve the resources allocation by formulating and solving an optimization problem, which is to minimize the total dwell time on all targets with the tracking accuracy of each target satisfying a pre-designed requirement. Since the Bayesian Cramer-Rao...
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...
A problem of state estimation with destination constraint is considered in this paper. An anti-radiation missile (ARM) often moves towards the target along a trajectory which is almost linear in the X-Y plane. The linear constraint for trajectory and target position are known as priori and can be used to enhance the performance of a tracking filter. In this paper, a destination constrained Kalman...
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...
The multiple hypothesis tracker (MHT) is a popular algorithm for solving multi-target tracking (MTT) problem in cluttered environment. It is known as a maximum a posterior (MAP) estimator which enumerates all possible global hypotheses and dedicates to find the most likely solution based on the received reports. However, its practical application is often limited by the complexity of data association...
The paper addresses the problem of distributed sensor fusion in the framework of random finite set. The Generalized Covariance Intersection (GCI) rule of multi-target densities is extensively used in multi-target Bayesian filtering scheme. But there are two problems in GCI which are unreasonable design of fusion weight and unable to tackle informative differentiation. In order to get rid of the bad...
This paper compares the tracking performance that can be achieved when using a nonlinear drag model for a helicopter, a constant drag motion model, and a baseline constant acceleration model. A particle filter is used for state estimation to address problems associated with nonlinear drag and nonlinear measurements of helicopter pose. We demonstrate that the inclusion of this nonlinear kinematic effect...
This article presents an information theory based sensor management method to be used for aerospace multi-target collaborative detection and tracking. The proposed sensor management method follows an information theoretic approach, in which PCRLB is used to calculate the tracking accuracy of multi-target. The detection particles are employed to determine the detection probability of incoming targets...
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 the multiple target tracking scenarios, the correct matching between targets and measurements is critical. There have been many approaches to resolve this problem called data association. In this paper, a regression method is proposed to resolve the data association problem. In the logistic regression model, nine potential predictor variables are designed which are related to the geometric information...
Aiming at the radiation control problem for sensor scheduling, a sensor scheduling algorithm based on partially observable Markov decision process (POMDP) is proposed. The target model is set up in the three-dimensional space, and the tracking task requirement is given by fuzzy logic theory. Then the radiation risk model is formulated as a POMDP, and the sensor radiation risk is dynamic updated by...
This paper considers the sensor selection problem for target tracking in large-scale sensor networks. We propose a new sensor selection strategy based on dual-criterion optimization. Both the bias change detection and information gain maximization are considered as criteria in our proposed sensor selection strategy. This new approach extends the sensor selection problem from single criterion optimization...
In this paper, we address the target detection problem using multi-sensor dynamic programming based track before detect (DP-TBD) methods. First, we give two implementation methods of multi-sensor DP-TBD under the centralized processing and the distributed processing, respectively. Then, in order to improve the implementation efficiency of the multi-sensor DP-TBD, we further propose an improved DP-TBD...
To address multi-sensor robust track-to-track association in the presence of sensor biases and missed detections, where sensors biases is time-varying and non-uniform, the target of different sensors is non-identical, the robust track-to-track association algorithm based on t-distribution mixture model is proposed. The robust track-to-track association problem is turned into the non-rigid point matching...
In order to filter tracks of ship targets for space-based maritime surveillance using electronic reconnaissance satellites, an extended Kalman filter (EKF) algorithm in geographic coordinates is proposed in this paper. Firstly, different methods of Dead reckoning (DR) are analysed in different coordinate systems. Then, the formula of EKF based on middle latitude sailing is derived. Finally, satellite-based...
Direction-of-arrival (DOA) estimation and tracking of signals using passive sensor arrays is a classic problem that becomes challenging when the number of sources varies over time and the signal-to-noise ratio is low. In this paper, we pose this problem as minimum mean OSPA (MMOSPA) estimation, which minimizes the the optimal sub-pattern assignment (OSPA) metric of the posterior random finite set...
This paper considers the state estimation of Markovian jump linear systems with random parameters and estimate feedback. The state estimate at the previous epoch is introduced into the dynamical model to depict some phenomena that the system evolvement may depend on the most recent estimate. Then, the linear minimum mean square error estimator is derived for the considered system. A filtering framework...
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, consensus-based Kalman filtering is extended to deal with the problem of joint target tracking and sensor self-localization in a distributed wireless sensor network. The average weighted Kullback-Leibler divergence, which is a function of the unknown drift parameters, is employed as the cost to measure the discrepancy between the fused posterior distribution and the local distribution...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.