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The state estimation of targets is a difficult task, particularly if the target exhibits nonlinear behaviour, which is often the case. Currently, the most popular filters used in target tracking are the Kalman filter (KF) and its various forms, as well as the particle filter (PF). Introduced in 2007, the smooth variable structure filter (SVSF) is a relatively new predictor-corrector method based on...
Tracking agile aircraft under high accelerations generally demands sophisticated models for determining trajectories with desirable dynamics and accuracy. Often this raises complexity of the estimation algorithm as it gives rise to more elaborated methods for both taking model nonlinearities into account and handling a greater number of state variables that describe the model. The approach of this...
This paper presents a method to achieve multi target tracking using acoustic power measurements obtained from an acoustic sensor network. We first present a novel concept called emitted power density (EPD) which is an aggregate information state that holds the emitted power distribution of all targets in the scene over the target state space. It is possible to find prediction and measurement update...
Recent research into multi-object filtering for non-standard targets introduced alternative approaches for target group representation. In these approaches a measurement model (likelihood) was suggested that led to a representation of the measurements as a spatial point process, namely a Poisson point process. In this paper we take a more traditional approach to extended target tracking. We assume...
Many well-defined metrics have been developed for data fusion problems in the target tracking domain. However, much less is known about the proper evaluation of Chemical, Biological, Radiological, and Nuclear (CBRN) data fusion methods. In this paper we begin to address the issue of evaluating the performance of CBRN fusion algorithms. As a demonstration of the applicability of modified target tracking...
In extended target tracking, targets potentially produce more than one measurement per time step. Multiple extended targets are therefore usually hard to track, due to the resulting complex data association. The main contribution of this paper is the implementation of a Probability Hypothesis Density (PHD) filter for tracking of multiple extended targets. A general modification of the PHD filter to...
Coherent decoys can induce anti-radiation missile (ARM) to the area outside radiant sources compared with the noncoherent decoys technology widely used now, the choke point of final utility of coherent decoy is the accurate control of radiant sources' phase difference. Model of two radiant sources decoying ARM is built in this paper, relationships between the phase difference of two coherent radiant...
An estimation fusion algorithm based on a group of hybrid coordinate (HC) filters is presented to the position and velocity estimation using angle-only measurements extracted from multiple maneuverable aircrafts with onboard passive sensor. The algorithm is a hierarchical architecture which consists of several local processors and a global processor. In each local processor, an extended Kalman (EK)...
Two main challenges lie in tracking the partially occluded targets in a high-similarity background: 1) similar intensities increase the difficulty of discriminating targets from the background, and 2) occlusion (illumination and shape) decreases the relativity of targets to templates. In this paper, a novel eigenspace-based hybrid particle filter tracking method combined with online non-local appearance...
Fusing out-of-sequence information is a problem of growing importance for multi-sensor target tracking systems due to sensors embedded in complicated network architectures. The problem of how to deal with these updates has received much attention in recent years and has been solved optimally and suboptimally by various authors. Most of the solutions treated only the problem of updating a track by...
In this paper, we focus on using the sensor network to track a moving target. We estimate the trajectories of moving targets by collecting the information from sensors measurements, and assume that sensors can be randomly moving within a limited radius r. Also assuming each sensor is able to calculate/obtain the distance between itself and the moving target. Here we introduce the modified particle...
Intelligent solutions for video surveillance require reliable object features for robust tracking. Surveillance cameras are generally low resolution and hence impose restrictions on the ability to identify sufficient features and descriptors for effective tracking. In such applications, reliable estimate of the object height from a single uncalibrated camera can prove to be a very useful feature....
The uncertainty of thrust acceleration will cause enormous error to model and track the accelerated motion of maneuvered target during orbit transfer process. An on-line minimum-variance estimator was developed for thrust acceleration applied to orbit transfer using discrete-time radar measurements. The mass-flow-rate of propellant was selected as a state variant, which was estimated by employing...
We propose a fusion framework to integrate multiple cues for tracking by finding a set of optimal dynamic weights for different tracking modalities. In the setup of Bayesian sequential estimation, we give an optimal criterion to find the dynamic weight for each modality: Using a linear combination of the proposal distributions from multiple cues to approach the posterior distribution p(xt|yt). The...
In multisensor target tracking systems measurements from the same target can arrive out of sequence. How to fuse out-of-sequence information is a very important problem for distributed multisensor target tracking systems. Local sensors send their track to a fusion center and then the fusing center uses these track data from one or more sensors to update. In this paper, we obtain the out-of-sequence...
In this paper, we proposed a novel method for single moving sound source tracking based on two successive algorithms. Although the MUSIC (multiple signal classification) method is well-known as one of the best high resolution methods for the unmoving source, two serious difficulties occur regarding as computational costs to solve the problem when the MUSIC method is applied in such a situation. The...
For target tracking applications it is a well-known technique to model the motion behavior by a finite set of motion models. This contribution discusses two cases in the area of local positioning where the measurement equation is taken from a finite set of possibilities, depending on the actual state of the object. The first case is a multi antenna scenario where it is unknown which antenna actually...
Ba-Tuong-Vo et al proposed a Bayes filter of single target in the random finite set framework. In this paper, we first extend the parameter mixture models (PMM) to state mixture models(s). And further an alternative derivation of a Bayesian tracking filter in clutter is proposed for single target. The key of the proposed algorithm is to derive the measurement likelihood function based on finite mixture...
In multisensor target tracking systems, observations produced by sensors typically arrive at a central processor out of sequence. There have been some update algorithms for single out-of-sequence measurement (OOSM). In this paper, we consider optimal centralized update algorithms with multiple asynchronous (different lag time) OOSMs. Firstly, we generalize the optimal update algorithm with single...
Sensor networks include large number of low cost sensor nodes with small processing capabilities that are deployed over an area in an attempt to do interest sensing task. In this paper we examine the role of very simple and noisy sensors for distributed tracking problem that is one of these tasks. We use a proposed binary sensor model, where each sensor's value is converted reliably to one bit of...
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