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We investigate the problem of determining the trajectory that an observer should follow to be able to accurately track a target in a bearings-only measurements context. We assume that the target's motion is uniform and that the measurements are corrupted by an additive Gaussian white noise. Though, in theory, this process is observable if the observer maneuvers with turns or accelerations, the quality...
In this paper, Multi-Task Linear Dependency Modeling is proposed to distinguish drug-related webpages that contain lots of images and text. Linear Dependency Modeling exploits semantic relations between images features and text features, and Multi-Task Learning takes advantage of metadata of webpages. Meaningful information of webpages can be made use of fully to improve classification accuracy. Experimental...
In order to solve the problem that asynchronous multi-source multi-track cannot be correlated effectively, a trajectory similarity model for asynchronous multi-source multi-track and a track correlation algorithm based on this model are proposed in this paper. Based on the idea of searching potential matched data points under spatial and temporal constraints, the optimal matched point is determined...
Dempster-Shafer (D-S) evidence theory is widely used for information fusion field. However, one of the main issues of D-S evidence theory is that, when large amount of focal elements in Basic Probability Assignment (BPA) are available, the fusion of BPA requires high computational cost and long computing time. This problem greatly limits its application. In this paper, a novel method for approximating...
This paper investigates the box-particle filter for multi-target tracking, and proposes a clustering based box-particle implementation of PHD filter. A subdivision step is added before the estimation of states. Each box is divided into several sub-box based on the estimated number of targets. An equivalent set of particles can be extracted from the set of subdivided boxes. Then, clustering technique...
In order to improve the comprehensive defense capability of netted radar system while tracking the multi-targets cooperatively, a more reasonable evaluation indicator is required to evaluate the overall performance of the netted radar system. The new evaluation indicators for radar deployment and allocation in the netted radar management are proposed quantitatively in this paper. As they consist of...
Cold atom interferometer is a promising technology to obtain a highly sensitive and accurate absolute gravimeter. With the help of an anomalies gravity map, local measurements of gravity allow a terrain-based navigation. We describe the model of the absolute gravity measurement. We develop a Laplace-based particle filter adapted to this context. This non-linear filter is able to estimate the positions...
In this paper, the maximum correntropy (MC) criterion is used as the cost function in the online sequential extreme learning machine (OS-ELM) algorithm and constraint OS-ELM (COS-ELM) algorithm, generating the proposed OS-ELM based on maximum correntropy (OS-ELM-MC) and COS-ELM based on maximum correntropy (COS-ELM-MC). In comparison with OS-ELM and COS-ELM, the proposed OS-ELM-MC and COS-ELM-MC present...
Device-free localization (DFL) is an emerging wireless localization technique where the target does not equip with any electronic tag for communicating with the localization system. It has been found numerous practical applications such as human health and medical care with the help of location detection and behavior analysis, intrusion detection, security safeguard, and emergency rescue. In the DFL...
With the exponential growth of web meta-data, exploiting multimodal online sources via standard search engine has become a trend in visual recognition as it effectively alleviates the shortage of training data. However, the web meta-data such as text data is usually not as cooperative as expected due to its unstructured nature. To address this problem, this paper investigates the numerical representation...
Medical image fusion technique plays an an increasingly critical role in many clinical applications by deriving the complementary information from medical images with different modalities. In this paper, a medical image fusion method based on convolutional neural networks (CNNs) is proposed. In our method, a siamese convolutional network is adopted to generate a weight map which integrates the pixel...
A novel random data association algorithm is proposed in the framework of multiple hypothesis tracking which can be equivalent to an NP-hard multidimensional assignment problem. The key idea of this new algorithm is to relax the multidimensional assignment problem to a linear programming problem. The solution of the linear programming problem may be treated as the probability of potential tracks,...
The square root unscented Kalman filter was introduced to provide a more numerically robust formulation of the unscented Kalman filter and to guarantee positive semi-definiteness. The filter maintains the Cholesky factor of the covariance matrix instead of the covariance itself. Efficient linear algebra techniques, including Cholesky update and downdate, are used to predict and update the Cholesky...
Different estimators have different optimization criteria according to the concrete application considered. Most existing metrics on estimation performance are some averages of estimation errors, which usually give “big” or “small” results to show the “bad” or “good” performance of the evaluated estimators. However, these metrics are only appropriate for measuring minimum mean-square error (MMSE),...
Since the significant intensity variations existed between different modal images, the deformable registration is still very challenging. In this paper, in order to alleviate the variations deficiency and attain robust alignment, we propose a multi-dimensional tensor based modality independent neighbourhood descriptor (tMIND) to measure the similarity between the images. The tMIND compares the neighboring...
Robust belief revision methods are crucial in streaming data situations for updating existing knowledge (or beliefs) with new incoming evidence. Bayes conditioning is the primary mechanism in use for belief revision in data fusion systems that use probabilistic inference. However, traditional conditioning methods face several challenges due to inherent data/source imperfections in big-data environments...
Dempster-Shafer(D-S) method has been used widely in fault diagnosis system of civil aircraft electrical system, but it has difficulty in dealing with combining evidences with high degree of conflict. In order to solve the problem, a new method is proposed in this paper. The proposed method in this paper introduces the historical data, defines the concept of modifying factor, and considers the influence...
A new pedestrian detection method is proposed on the slope using multi-layer laser scanner in this paper. Firstly, the parameters of the slope scene are obtained from the priori point cloud. Then use the scene parameters to eliminate the ground returns by Elevation-like Map. After segmentation a nonparametric kernel density estimation method is proposed to extract the position of person by fusing...
Single-image blind deblurring could be considered as an important preprocessing step in imaging information fusion. Its purpose is to simultaneously estimate blur kernel and latent sharp image from only one observed blurred image. Blind deblurring has been attracting increasing attention in the fields of image processing, computer vision, computational photography, etc. However, it is a typically...
Acoustic propagation delay has not been investigated for a continuous wave multistatic sonar tracking system except for the recent study conducted by Jauffret et al. [4], which estimates the trajectory of a constant velocity target. The results showed that the estimate bias caused by the propagation delay is not negligible, especially for a bistatic system. This paper develops an interacting multiple...
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