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How can teams of artificial agents localize and position themselves in GPS-denied environments? How can each agent determine its position from pairwise ranges, own velocity, and limited interaction with neighbors? This paper addresses this problem from an optimization point of view: we directly optimize the nonconvex maximum-likelihood estimator in the presence of range measurements contaminated with...
Obstacle detection and tracking is a fundamental task for several Advanced Driver Assistance Systems (ADAS) and self-driving cars. Several approaches have been presented in the literature in the last years and many of them are based on visual sensors. In this paper we propose an approach that uses only stereo cameras to detect and track obstacles and compute visual odometry to get the vehicle's ego-velocity...
Kalman Filters are utilised for filtering and estimation in a large set of application. Here, this methodology is utilised for trajectory estimation of an underwater robot. In this work, three Kalman Filter methods are proposed for trajectory estimation. There are: Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF) and Central Difference Kalman Filter (CDKF). Simulation results are presented...
Multi-target tracking is a challenging problem in video surveillance. The paper presents a multi-target tracking algorithm based on optical flow histogram and Kalman filtering. The method we proposed can effectively improve the tracking accuracy. First, targets are detected by Gaussion mixture model in real time. Second, a trajectory is initialized when a new target appears. Meanwhile, Kalman filtering...
Fully automated vehicles and mobile robots operate in a shared environment with pedestrians. To minimize the risk for pedestrians, it is very important to track them in a precise way. As cameras are often installed in surveillance situations, they are used for tracking pedestrians in a shared environment. To improve the accuracy of the tracking, it is necessary to include all available context information...
In this paper localization using UWB positioning system and an inertial unit containing a single accelerometer is considered. The main part of the paper describes a novel algorithm for person localization. The algorithm is based on modified Extended Kalman Filter and utilizes TDOA (Time Difference of Arrival) results obtained from UWB system and results of acceleration measurement performed by the...
In this paper a concept of hybrid Bluetooth Low Energy (BLE) Ultra-wideband (UWB) positioning system is presented. The system is intended to be energy efficient. Low energy BLE unit is used as a primary source of measurement data and for most of the time localization is calculated based on received signal strength (RSS). UWB technology is used less often. Time difference of arrival (TDOA) values measured...
In this paper, we consider parameter estimation in latent, spatiotemporal Gaussian processes using particle Markov chain Monte Carlo methods. In particular, we use spectral decomposition of the covariance function to obtain a high-dimensional state-space representation of the Gaussian processes, which is assumed to be observed through a nonlinear non-Gaussian likelihood. We develop a Rao-Blackwellized...
Detection of falling is an important research issue to develop smart healthcare technologies for elderly people as the population is rapidly increasing. To achieve the goal, accurate human tracking is imperative to detect a fall regardless of distance and occlusions. However, existing technologies are focusing on either 2D tracking with a single camera or 3D tracking using a depth camera (distance...
One of the algorithms implemented in Radar system is Kalman filter. Kalman filter is one of a method to estimate a problem in dynamic systems and model measurement. Kalman filter has the ability to estimate certain condition either in the past, current, future time, or characteristic of the model unknown. The Purpose of this paper is to design ships tracking system using Kalman filter algorithm. According...
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...
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...
This paper presents navigation and control of a robot for capturing a moving target using the vision system. A stereo camera is used to calculate the pose of the moving target (position and orientation). An Adaptive Unscented Kalman Filter (AUKF) is used to generate an optimal path to capture the moving object by estimating the state vector (position, orientation, linear and angular velocities) of...
In this paper, a plain data-driven and simulation-based approach to object tracking is investigated. The basic idea is to use the probabilistic model of the tracking problem to simulate a large amount of state and observation sequences. Both are fed into a regression algorithm that learns a mapping from the observations to the states. In particular, we consider random forest regression and apply it...
Variable structure filter (VSF) is a robust filter for linear uncertain system. In order to remove the chattering caused by high-frequency gain switching of VSF, the smoothing boundary layer (SBL) has been introduced. And similar to Kalman filter, the optimal state estimation of VSF can be got at the optimal smoothing boundary layer (OSBL). However, in practical applications, the statistical characteristics...
In this article, an approach for multi-vehicles localization and guiding is described and demonstrated with experiments in real conditions. The general methodology of the presented work is based on a top down approach implemented in each vehicle of the fleet and having a map of the environment to estimate the absolute localization of each vehicle. The principle is to select, at each time, the best...
The paper addresses a problem of ballistic object trajectory estimation on the basis of measurements from a cinetheodolite electro-optical tracking system. The object flight dynamics is modeled using a three degrees of freedom equations of motion. The estimation of object trajectory is performed with the use of an Extended Kalman Filter.
We present an algorithm that allows an interceptor aircraft equipped with an airborne radar to meet another air target (the intercepted) by developing a guidance law and automatically adapting and optimising the transmitted waveform on a pulse to pulse basis. The algorithm uses a Kalman filter to predict the relative position and speed of the interceptor with respect to the target. The transmitted...
The paper presents a concept of the parametric autofocus method for Passive Inverse Synthetic Aperture Radar (ISAR) imaging of air targets. To create a focused ISAR image, the precise knowledge of an object trajectory is required. In this paper a theoretical model of the target motion and an algorithm for finding the best set of estimated motion parameters are described. Simulated results of ISAR...
Nowadays, mobile devices are equipped with a number of radio transceivers which are active every day and everywhere. As a result, vast amounts of data and technical logs are collected by mobile operators. For this reason, mobile phones have a great potential for sensing urban and rural mobility and population displacement. Therefore, in this article, we are proposing a new approach for estimating...
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