The proceedings contain 23 papers. The topics discussed include: capturing dynamics on multiple time scales: a multilevel fusion approach for cluttered electromagnetic data;classification of terrain using multi-resolu...
ISBN:
(纸本)9780819481740
The proceedings contain 23 papers. The topics discussed include: capturing dynamics on multiple time scales: a multilevel fusion approach for cluttered electromagnetic data;classification of terrain using multi-resolution satellite/aerial imagery and lidar data;data fusion and classification using a hybrid intrinsic cellular inference network;fusion of ESM reports through Dempster-Shafer and Dezert-Smarandache theories;level 0-2 fusion model for ATR using fuzzy logic;multi-layered context impact modulation for enhanced focus of attention of situational awareness in persistent surveillance systems;global evaluation of focused Bayesian fusion;multiple hypothesis tracking of two persons using a network of lidar sensors with stationary and directional beams;a copula-based semi-parametric approach for footstep detection using seismic sensor networks;and integrating perception and problem solving to predict complex object behaviors.
The technique of data fusion is a new kind of data processing technique and has broad appliance foreground. Appearance of stealthy and disturbed targets in modern battlefield leads to data extraction and fusion by net...
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The technique of data fusion is a new kind of data processing technique and has broad appliance foreground. Appearance of stealthy and disturbed targets in modern battlefield leads to data extraction and fusion by networking various sensors to maximize use of information to perform recognition, orientation and tracking of targets. As we known well, radar only acquire angle information without range information when encounter noise suppress jammer. Netted radars could get position information of interference by make use of radars position relatively and target angle information. Yet if there is more than one target, the orientation of targets could error due to orientation confuse. The paper present methods that through association arithmetic of kalman filter to avoid confuse.
In a distributed estimation or tracking system, the global estimate are generated by the local estimates. Under the assumption of independence cross sensor noises, Bar-shalom proposed a two sensor tracking fusion form...
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In a distributed estimation or tracking system, the global estimate are generated by the local estimates. Under the assumption of independence cross sensor noises, Bar-shalom proposed a two sensor tracking fusion formula, which used only the inverses of covariances of single sensor estimation errors. In this paper, we present more general multi-sensor estimation fusion formula, where the assumption of independence cross sensor noises and the direct computation of the generalized inverse of joint covariance of multiple sensor estimation errors are not necessary. Instead, as the number of sensors increases, a recursive algorithm is presented, in which only the inverses or the generalized inverses of the matrices having the same dimension as that of the covariance matrices of single sensor estimate errors are required.
This paper analyzes the beamforming separation effectiveness of several different microphone array configurations. These configurations consist of 4, 8, and 16 microphones placed in a plane for two-dimensional speech ...
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This paper analyzes the beamforming separation effectiveness of several different microphone array configurations. These configurations consist of 4, 8, and 16 microphones placed in a plane for two-dimensional speech separation, with inter-microphone distances varying from 10cm to 160cm in logarithmic step sizes. It is discovered that the linear and bilinear arrays result in the largest signal-to-noise ratio (SNR) gain after delay-and-sum beamforming in the case of speech signal and speech noise. Also, simulations show that larger inter-microphone distances result in a higher SNR gain, although the practicality of the higher inter-microphone distances is limited for certain applications where the array size is constrained.
This paper presents a novel approach to: 1) distinguish military vehicle groups, and 2) identify names of military vehicle convoys in the level-2 fusion process. The data is generated from a generic Ground Moving Targ...
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This paper presents a novel approach to: 1) distinguish military vehicle groups, and 2) identify names of military vehicle convoys in the level-2 fusion process. The data is generated from a generic Ground Moving Target Indication (GMTI) simulator that utilizes Matlab and Microsoft Access. This data is processed to identify the convoys and number of vehicles in the convoy, using the minimum timed distance variance (MTDV) measurement. Once the vehicle groups are formed, convoy association is done using hypothesis techniques based upon Neyman Pearson (NP) criterion. One characteristic of NP is the low error probability when a-priori information is unknown. The NP approach was demonstrated with this advantage over a Bayesian technique.
In this paper, a new approach to logic-based knowledge fusion is proposed. It is based on the use of (a form of) semaphores to solve conflicting information. It is shown that a traditional use of semaphores is not rel...
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ISBN:
(纸本)0819449598
In this paper, a new approach to logic-based knowledge fusion is proposed. It is based on the use of (a form of) semaphores to solve conflicting information. It is shown that a traditional use of semaphores is not relevant in the case of an iterated fusion process. Accordingly, an adequate technique is thus proposed that allows multiple fusion steps to be performed. Technical properties of this new technique are then investigated.
Mutual-aided target tracking and target identification schemes are described by exploiting the couplings between the target tracking and target identification systems, which are typically implemented in a separate man...
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Mutual-aided target tracking and target identification schemes are described by exploiting the couplings between the target tracking and target identification systems, which are typically implemented in a separate manner. A hybrid state space approach is formulated to deal with continuous-valued kinematics, discrete-valued target type, and discrete-valued target pose (inherently continuous but quantized). We identify and analyze ten possible mutual aiding mechanisms with different complexity in different levels. The coupled tracker design is illustrated within the context of JointSTARS using GMTI and HRRR measurements as well as digital terrain and elevation data (DTED) and road map among others. The resulting coupled tracking and identification system is expected to outperform the separately designed systems particularly during target maneuvers, for recovering from temporary data dropout, and in a dense target environment.
This paper describes a series of experiments in data fusion. of remotely sensed multispectral satellite imagery, in-situ physical measurement data (temperature, pH, salinity), and implicitly encoded knowledge (contain...
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ISBN:
(纸本)0819449598
This paper describes a series of experiments in data fusion. of remotely sensed multispectral satellite imagery, in-situ physical measurement data (temperature, pH, salinity), and implicitly encoded knowledge (contained in location and season) to predict values and classified levels of chlorophyll-a using an artificial. neural net (ANN). ANNs inherently fuse data inputs and discover relationships to provide a fused interpretation of the inputs. The experiments investigated the effects of fusing data and knowledge from the three different types of sources: non-contact, physical contact, and implicit. The results indicate that fusing the three source types improved prediction of chlorophyll-a values and classification levels, and that the multisource ANN fusion approach might improve or augment present periodic sample point monitoring methods for chlorophyll-a.
Various fusion system architectures postulated and studied previously for environments with two and three data sources are further explored in this study to bring out the expanding scope for delineating the architectu...
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ISBN:
(纸本)0819449598
Various fusion system architectures postulated and studied previously for environments with two and three data sources are further explored in this study to bring out the expanding scope for delineating the architecture options for multiple data source environments. A spectrum of single and multi-stage fusion architecture options are defined. The potential for such expansion of choices is illustrated using the scenario with four data sources as an example. Potential problem environments corresponding to this range of two to four data sources are identified. Various fusion logic strategies that can be brought to bear for the analysis of these fusion architecture options, when these fusionarchitectures are employed for Decisions In - Decision Out (DEI-DEO) fusion, are also discussed.
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