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In traditional DV-Hop localization algorithm, the average estimation hop distance is greater influence for the distribution of beacon nodes, which causes high positioning error. A new algorithm is proposed to improve this disadvantage. The new improved algorithm uses the hyperbolic method to locate the unknown node position. This way eliminates the cumulative error and improves the positioning accuracy...
This paper presents a new target tracking method. The presented method which named marginalized cubature Kalman filter is based on standard cubature Kalman filter and marginalized moment estimator. The marginalized moment estimator uses sigma-points sampling and Guass-Hermite integration to estimate the mean and covariance. The proposed algorithm which is called MCKF in short, uses marginalized moment...
After capturing the tracking satellite, the target satellite will turn into a compound satellite, and the inertia parameters of target satellite can produce great changes and greatly affect the attitude control system and its control effect. In order to estimate the inertia parameters of target satellite, two methods including the method based on Angular Momentum Conservation Law and the modified...
The paper proposes a ground moving target detection and estimation method aiming at Ultra Wide Band and -Beam (UWB) Synthetic Aperture Radar (SAR) systems. The method is developed on the moving target detection by focusing technique and requires a SAR system flying with two different speeds during the integration time. The method allows us to detect ground moving target, even hidden by clutter, and...
Marine ranching is a new concept of modern fishery, which has extremely significance to the development of modern ocean economy. Various technologies are required to ensure the efficiency of marine ranching. Among those, the technology of ocean resource assessment, especially fish resource, plays an indispensible and key role. This paper introduces an effective and precise method to assess the fishery...
Accurate object tracking has become increasingly important with developments in Lidar and high-resolution camera systems for remote surveillance. Typical methods utilize Markov Chain state estimation paired with Kalman or particle filters. These methods, however, are susceptible to loss of track if an error is encountered or a loss of image occurs. We developed a set of algorithms built on more recent...
This paper reviews sensor selection methods for distributed detection, distributed estimation and distributed tracking in wireless sensor networks. Before the discussion of different sensor selection methods, brief introductions of distribution detection, distribution estimation and distributed tracking are presented respectively. Future research directions are also given to facilitate further research...
The employment of embedded passive sensors in order to perceive environment for reducing the accident risk level is a tendency of intelligent vehicles research. From such sensors, one can extract useful informations which can assist the driver to identify hazardous situations. While safety improvement is a substantial requirement for driving assistance, localizing and tracking obstacles in complex...
The main focus of this paper is on the estimation of target motion parameters using bearing measurements. Here, based on a linearization of measurements, a recursive least squares (RLS) solution is developed. The performance of the proposed method is compared to PLE which uses the same approach in measurement linearization. Simulation results show the excellence of the proposed method over the PLE,...
A guidance law of the missile interceptor with passive ranging system (e.g. image IR seeker) based on second-order sliding mode is proposed in this paper. The missile system equipped with the passive ranging system can provide good stealth ability during its course of tracking the trajectory of a maneuvering target, therefore enhancing the probability of successful interception. The passive ranging...
Estimating the position of a moving target in the polar frame of reference has been a major problem in the conventional tracking systems. The commonly used sensor equipment provides the position of target in polar coordinates i.e. in range and azimuth (or bearing) angle with respect to the sensor location. The use of simple Kalman filter increases the error in this case. For more accurate tracking,...
In ground target tracking based on kinematic measurements by airborne radar, several challenges in general strongly deteriorate the performance of any standard tracking filter. The major challenges are imprecise measurements and missed detections, a strong false alarm background, closely-spaced targets, technical and terrain obscuration, and complex target motion. In order to counterbalance such a...
In this paper we propose a novel real time approach to localize and track a target using sparsely (non-overlapping) deployed binary sensors. Each of these sensors reports 1-bit information regarding a target's presence or absence within its sensing range. Our technique estimates the distance covered by a target on the basis of the time it spends in the sensing region. The trajectory of the target...
To accommodate the model mismatch in clutter rate, a cardinality probability hypothesis density (CPHD) filter with unknown clutter rate has been proposed by Mahler. It has proved to be a promising algorithm for multi-target tracking in complex environment. However, in Mahler's algorithm, the calculation of the number of clutters without observations is determined by the hybrid cardinality distribution...
In this paper, performance of Gauss-Hermite filter (GHF) in bearing only tracking problem has been compared with that of extended Kalman filter (EKF) and unscented Kalman filter (UKF) in terms of estimation accuracy, probability of track-loss and computational efficiency. The performance improvement of the GHF with increase in quadrature points and enhanced robustness compared to EKF and UKF with...
A Wireless sensor network (WSN) can be deployed in advance for tracking a moving target. The sensor nodes can be arranged at some expected positions, the computing complexity for locating the target hereby will be mitigated. In this paper, we propose a cooperative framework for multiple sensor nodes to track the moving target. A lightweight distributed method to locate the target is presented in the...
A method derived from the Sequential Monte Carlo approaches is proposed here to solve the vehicle detection and tracking problem using a scanning laser rangefinder. The originality of this approach lies in a joint detection and tracking of the objects that avoid the usual pre-detection stage. The proposed modeling is strongly nonlinear. To improve the efficiency of the solution, we use a Rao-Blackwell...
The Multiple Hypothesis Tracker (MHT) and the Cardinalized Probability Hypothesis Density (CPHD) are two algorithms which can overcome the Multi-Targets Tracking (MTT) issues in automotive applications. This paper describes the performance of such algorithms and, in particular the Gaussian Mixture Probability Hypothesis Density (GMPHD) filter and the Track Oriented Multiple Hypothesis Tracker (TOMHT)...
In the target tracking and its engineering applications, recursive state estimation of the target is of fundamental importance. This paper presents a recursive performance bound for dynamic estimation and filtering problem, in the framework of the finite set statistics, for the first time. This performance limit is derived based on the meaningful distance error between two random sets, the target...
This paper deals with the problem of Distributed Estimation (DE) in binary Wireless Sensor Networks (WSN). Specifically, we propose to enhance the well-known Sign Of Innovation (SOI) based Extended Kalman Filter (SOI-EKF) [1] using the Unscented Transformation (UT) and iterative processing. The unscented transformation is especially used here to boost the quality of the predicted observation, already...
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