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This paper addresses the problem of joint detection and estimation fusion when sensor quantized data are correlated in the distributed system. The traditional methods to handle this joint problem tend to treat the detection and estimation tasks separately, which put more emphasis on the detection part but treat the estimation part sub-optimally. In this work, the joint detection and estimation fusion...
In this paper, we consider the source localization problem in which several microphones collaborate to locate an active sound source in a reverberant environment. Sound source localization (SSL) based on the Generalized Cross Correlation (GCC) function is widely studied for the past few decades. However, in a reverberant environment, the maximal peak of the GCC function does not necessarily correspond...
In the presence of strong noise or reverberation, the acoustic source localization and tracking problem is confronted with severe challenges. One of them is that the maximal peak of the localization function may not be generated by the real source. In this paper, the stochastic region contraction (SRC) is adopted to search for multiple peaks of the localization function rather than the maximal one...
This paper deals with sound source localization and number estimation in indoor environments using a circular microphone array. Multiple sound source localization is achieved by performing single source localization at each selected time-frequency (TF) point of received signals after short-time Fourier transform. A TF point selection method is proposed to reduce the computational time, which depends...
In this paper, we address the problem of the joint detection and estimation fusion in distributed multiple sensor systems. The objective is to decide between two hypotheses and make the corresponding estimates if the decided hypothesis has unknown parameters at the same time. The fusion system comprises N independent sensors, and each one sends a binary decision to the fusion center for integration...
In this paper, the problem of estimating the directions of arrival (DOAs) for an unknown number of sound sources is addressed using a microphone array. In outdoor environments, the reverberation is not considered, so the pure delay mixture model is typically adopted here. Since the sound signal is usually wide-band and non-stationary, the Short Time Fourier Transform (STFT) is employed. However in...
In extended target tracking, it is a critical step to implement the measurement set partitioning, which aims to partition the whole measurement set into several distinct clusters. When multiple extended targets are in close proximity, there are great challenges. To deal with this problem, we introduce the DBSCAN-FCM partition to the Gaussian inverse Wishart PHD (GIW-PHD) filter, which combines the...
The paper presented an extension of random matrix-based approach [1] to track multiple extended targets in the cluttered environment, which can provide the estimates for target kinematics and target extension, as well as the corresponding identity information. To do this, the DBSCAN clustering (Density Based Spatial Clustering of Applications with Noise) method is employed to divide the whole measurement...
This paper is concerned with performing the measurement-to-measurement association and bias estimation jointly in the presence of missed detections. An integrated mix integer programming (MINLP) model is established to determine the correspondence between local measurements and estimate sensor biases simultaneously. An alternation optimization mechanism is employed to solve the complicated MINLP model...
The paper addresses the problem of estimation fusion in sensor network, in the presence of possible biased local estimates. A sensor selection-based fusion scheme is presented to deal with this problem, which seek to select a subset of sensors to be fused, for the purpose of achieving a better estimation performance. Firstly, we introduce an optimization criterion over any given subset of sensors...
This paper presents an approach to track an unknown number of extended targets, in the presence of clutter measurements and missed detections, where the extensions of targets are modeled as random hypersurfaces. The random hypersurface model developed recently by Baum et al. is embedded into the extended target PHD framework. To do this, the pseudo-measurement and measurement likelihood function for...
Track to track association problem is crucial for multisensor data fusion, and become complicated in the presence of sensor bias, random errors, false tracks and missed tracks. In this paper, we apply the optimal Bayes joint decision and estimation(JDE) which was proposed in [12] to the track-to-track association in the presence of sensor bias and develop a simplified JDE. The optimal Bayes JDE accounts...
Gaussian mixture is an important probability representation for the system state in many applications, especially used to model a complex density. The common drawback of Gaussian mixture representation is that the component number may grow rapidly in case with the recursive processing of Gaussian mixture. Therefore, it is extremely important to develop an efficient Gaussian Mixture Reduction (GMR)...
Multiple control valve which is a complex hydraulic control block is widely used in mobile hydraulic equipment. Design and pro-actively incorporate functional performance into the mobile hydraulic system is usually a difficult mission for the design engineer. Present paper setup an integrate design and Evaluation platform of multiple control valve based on the intelligent simulation package AEMSim...
Analyzing the characteristics of ancient books and the construction, the function, the characteristics of digital library, the paper constructs a efficient digital model, then discusses digitized description, digital storage, digital accessing to implement the model. On the basis of that, the paper constructs a Storage Area Net strategic framework to storage massive information
A target is denoted extended when the target extent is larger than the sensor resolution. A tracking algorithm should be capable of estimating the target extent in addition to the state of the centroid. This paper addresses the problem of tracking an extended target with unknown parameter about the target extent. The extended target is regarded as a spatial distribution model, and the target extent...
A component pruning algorithm based on entropy distribution is proposed for the Gaussian mixture implementation of probability hypothesis density filter. Maximum a posterior criterion is adopted for the estimation of mixing parameters. Entropy distribution with negative exponent parameters, which only depends on mixing weights, is adopted as the prior distribution of mixing parameters. The update...
Multi-target tracking is a difficult problem due to the measurement origin uncertainty. Recently, the probability hypothesis density (PHD) filter provides a promising tool for joint estimation of target number and multi-target states, without using data association technique. In particle implementations of the PHD filter, clustering is used to extract the target state from the particle population...
Due to the astonishing development in memory and processing capabilities of hand held devices such as smart phones, it is not a dream anymore to enable mobile devices not only as conventional web service requesters but even as providers. The willingness and enthusiasm of service providers place abundant services at the disposal. But this abundance makes the efficiency of service discovery a critical...
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