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This paper presents a novel method for tracking multiple extended objects. The shape of a single extended object is modeled with a recently developed approach called Random Hypersurface Model (RHM) that assumes a varying number of measurement sources to lie on scaled versions of the shape boundaries. This approach is extended by introducing a so-called Mixture Random Hypersurface Model (Mixture RHM),...
Machine vision systems have been designed for automated monitoring and analysis of social behavior in Drosophila by Herko Dankert. The Ctrax (The Caltech Multiple Fly Tracker) is implemented for tracking the Drosophila's movement. But the machine vision method is so sophisticated that it is hard to use by a researcher who is lack of computer technology knowledge. Likewise, most of the machine vision...
An effective way of overcoming the observability problem in single sensor passive tracking is to fuse information from multiple passive sensors. However, new challenges arise from the fact that sensor information must be transmitted between sensors, often over severely limited communication channels. In this paper, we address the issue of how such communication channels can be used to greatest effect...
This paper describes a new efficient approach to the conventional nonlinear tracking problem in a nongaussian setting that consists in the transformation of the nonlinear output measurement function in a linear form by the definition of a virtual measurement process. Such a procedure leads to the use of an efficient filter capable to take into account the nongaussanity of the transformed measurement...
This paper investigates the use of a sensor network for localizing and tracking a moving target using only binary data. Due to the simple nature of the sensor nodes, sensing can be tampered (accidentally or maliciously), resulting in a significant number of sensor nodes reporting erroneous observations. Therefore, it is essential that any event tracking algorithm used in Wireless Sensor Networks (WSNs)...
Bearings-only tracking is a challenging estimation problem due to the variable observability of the underlying targets. In the presence of false alarms and missed detections, the difficulty of the estimation problem is further compounded by the presence of ghost targets. This paper presents a solution to the bearings only tracking problem based on the theory of random finite sets or Finite Sets Statistics...
Under a complex environment, robust visual tracking is a challenging problem due to the presence of noise, occlusion and variation of illumination. The recently proposed compressed sensing based tracker, has overcome these difficulties to a remarkable extent. Under such framework, it actually assumes that the coding residual follows Gaussian or Laplacian distribution, which may not be general enough...
Technical means to improve radar tracking accuracy by way of wideband frequency agility is analyzed, and practical implementation and test results of an 8∼18GHz ultra-wideband (UWB) frequency agility monopulse tracking radar are provided.
In this paper, we consider the robust Kalman filtering based track fusion problem in multi-sensor network. We deal with the dynamic systems when the convariance of the measurement noises suffers norm-bounded uncertainties and propose a minimax robust track fusion method by minimizing the worst-case fusion error variance for all feasible noises covariance matrix. The numerical simulations demonstrate...
Target tracking is a well studied topic in wireless sensor networks. However, uncertainty existed in sensor networks presents new challenges for it. Besides the energy conservation of networks, target tracking has to deal with different kinds of uncertainty, such as the impreciseness of positioning systems, environment noise and limited sensitivity of sensors. In this paper, we study the problem of...
Camshift is an effective algorithm for real time dynamic target tracking applications, which only uses color features and is sensitive to illumination and some other environment factors. When similar color existing in the background, traditional Camshift algorithm may fail, that is the target getting lost. To solve the problem, an improved Camshift algorithm is firstly proposed in this paper to reduce...
A nonlinear system gives rise to many inherent difficulties when designing a feedback control. Motivated by a fixed-speed, fixed-altitude Unmanned Aerial Vehicle (UAV) that tracks an unpredictable target, we seek to control the turning rate of a planar Dubins vehicle. We introduce stochasticity in the problem by assuming the target performs a random walk, which both aides in the computation of a smooth...
In this paper, we investigate target tracking with adaptive sampling in order to optimize the use of expensive and limited resources that Autonomous Vehicles (AVs) have at disposition in pursuit-evasion games. An adaptive sampling policy is developed in order to minimize energy consumption while satisfying performance guarantees such as, increased probability of detection over time, and maintenance...
This paper proposes an Extended Kalman Filter (EKF) based approach to track a moving target UAV in 3D. The state of the target UAV is estimated from the range, azimuth, and elevation angle measurements that are assumed to be available from a ground based sensor or from on-board seeker antenna. The chaser vehicle states are also estimated using onboard sensors, namely GPS + IMU. These estimated states...
In this paper a new association probability was proposed to enhance the accuracy and stability of the probabilistic data association filter results in dense clutter environment. Firstly, the most popular data association algorithms (nearest-neighbor standard filter and probabilistic data association) were introduced, and then the advantages and disadvantages about these tow algorithms were analyzed...
For distributed underwater target localization system, targets correlation is one of the key technologies. In this paper, the feature spectrum extraction and targets correlation method were introduced. The sea trial recording data processing results proved the method was feasible and could be used in distributed detection and localization system.
Determining the motion pattern of laboratory animals is very important in order to monitor their reaction to various stimuli. In this paper, we propose a robust method to track animals, and consequently determine their motion pattern. The method is designed to work under uncontrolled normal laboratory conditions. It consists of two steps. The first step tracks the animal coarsely, using the combination...
A simple and fast algorithm for tracking multiple targets in real-time traffic scene is presented. The connected domains of moving objects, which are segmented out by the adaptive background subtraction algorithm, are obtained by morphological operation and resolution reduction. Then the track-association algorithm is applied to track the targets. The experimental results show that the proposed method...
This paper proposes a new self-tuning Kalman filter with good tracking ability for unknown noise statistics and unknown abrupt input change. The new filter can easily compute unknown abrupt input and steady-state gain matrix by building up online identification of ARMAX innovation model in real time. The simulation results of tracking a maneuvering target shows the effectiveness of the new method...
Current statistical model actually is a modified Singer model, its mean value is the forecast value of current acceleration, the random maneuvering acceleration is still supposed to one order time correlative process in time axis. Because current statistical model can identify the maneuvering acceleration online and adjust the state noise covariance matrix, it is more close to reality compared to...
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