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This paper will specifically undertake the task of improving the passive sonar system using self-organizing map. Localizing multiple targets is a challenging problem as passive sonar sensors are only able to detect the targets' bearing angle. An effective way to find the targets location is by triangulation. However, in multi-sensor multi-target environment, ghost targets are introduced during the...
Recent developments in image fusion have produced a variety of approaches like image overlay, image sharpening, and image cueing through pixel, feature, or region/shape combinations. The applicability of these approaches and techniques differ on the image content, contextual information, and generalized metrics of image fusion gain. An image fusion gain can be assessed relative to information gain...
A crucial point in the decision-level identity fusion is to combine information in an appropriate way to generate an optimal decision, according to the individual information coming from a set of different sensors. An interesting approach was developed for the decision- level identity fusion, which use optimization techniques to minimize an objective function which measure the dissimilarities between...
Works have investigated the problem of the conflict redistribution in the fusion rules of evidence theories. As a consequence of these works, many new rules have been proposed. Now, there is not a clear theoretical criterion for a choice of a rule instead another. The present paper proposes a new theoretically grounded rule, based on a new concept of sensor independence. This new rule avoids the conflict...
This paper presents a fusion process developed for the future armoured vehicle system (FAVS) technical demonstration (TD) project. One of the project objectives was to develop, optimize and demonstrate a multi-sensor suite mounted on an army vehicle to detect and identify targets while the platform was moving. The sensors consisted of a cooled infrared camera, millimetre-wave radar and a defensive...
This paper presents a novel sequential variational inference algorithm for distributed multi-sensor tracking and fusion. The algorithm is based on a multi-sensor target representation where a target is represented jointly by its states at different sensors and a global state fusing all sensor data. A tree-structured graphical model is adopted to model the dependencies between these states at a time...
This paper studies the feasibility of information analysis processing technology, which fuses speech and image together in the real-time monitoring system. It emphasizes particularly on speech analysis and fuses these two technologies in terms of scoring strategy. It also makes some improvement on MFCC feature extraction and proposes a quick MFCC algorithm. The proposed algorithm can reach the requirement...
In the sense of likelihood ratio test (LRT), a new type of distributed constant false alarm rate (CFAR) scheme-CCAWCA(censored cell-averaging -R-weighted cell averaging) CFAR detector is presented Its characteristic is that censored cell-averaging (CCA) CFAR algorithms are used in local processors to form the estimation of SNR of local observations, and then the estimation transmitted to the data...
The formalization of network centric warfare (NCW) signaled a new Department of Defense drive towards systems that could conceivably interact towards the accomplishment of a common goal. But the debate regarding NCW possibilities and practicalities in terms of existing and potential technologies highlight that much work is needed before the theortical NCW can be realized. The Information and Cyberwarfare...
The contemporary operating environment (COE) imposes significant challenges for military personnel and systems. The asymmetric nature of the threat and the proliferation of sophisticated weapon systems to rogue nations and trans-national terrorist organizations only further the need to ensure friendly forces maintain a high-level of warfighter readiness. As this threat evolves the importance of higher-level...
The fundamental point of this paper is that the fusion of several simple, somewhat unreliable, and somewhat inefficient frontal face detectors results in an efficient and reliable frontal face detector which, without any training, performs similarly to a state-of-the-art neural network based face detector trained on 60,000 images. The simple detectors used include a skin detector, symmetry detectors,...
In this paper, we present two novel methods to handle the fusion of multiple Bayesian Network knowledge fragments which we termed N-Combinator and N-Clone. In DSO National Laboratories, we have developed a cognition based dynamic reasoning machine called D'Brain capable of performing high level data fusion. Knowledge is encapsulated in D'Brain as Bayesian Networks knowledge fragments. D'Brain is dynamic...
An new object oriented development suite for data fusion is presented. It is shown how the various issues in the data fusion development like design, implementation, simulation and testing are realised and automated by this development suite. This allows the realisation of high sophisticated data fusion systems as applied in numerous civil and defence areas, like air traffic or satellite orbit control,...
The first challenge in crisis response management is the early damage and needs assessment based on all incoming information from various sources such as on field deployed sensors or human observations. Likewise, it is important for an efficient crisis response management to make sure that ambiguous terminology is clearly defined, and methodologies and indicators explained. To support the damage assessment,...
Information fusion is a key factor for insuring information superiority in various military and civil surveillance systems. Military applications may be found in air defence, force and convoy protection, and combat management systems for naval ships. Coastal and urban surveillance, air traffic control, and Harbour protection address more civil areas. A new aspect in all these applications is the issue...
Probabilistic multi-hypothesis tracking (PMHT) is an algorithm for tracking multiple targets when measurement-to- target assignments are unknown and must be jointly estimated with the target tracks. Multi-frame assignment PMHT (MF- PMHT) is an algorithm designed to mitigate some performance problems associated with PMHT. In MF-PMHT, the PMHT algorithm is applied to multi-frame sequences in the last...
PMHT algorithm, as proposed, promises high performance multi target tracking in clutter with (relatively) modest computational resources. However, when applied to practical target tracking situations, a number of problems need to be overcome. PMHT assumes fixed number of tracks, and furthermore it assumes that all tracks are true tracks. No track quality measure is provided within PMHT to enable false...
Prior to committing personnel to investigate a building or suspicious site such as a cave, it is imperative to determine the importance and current danger of the site. To this end, sensors on a robotic platform can interrogate the site prior to sending in personnel. This paper investigates methods to exploit multiple sensor modalities in order to automatically 1) detect human presence, and 2) detect...
In this paper we present an application that utilizes a novel two-level fusion architecture to detect and track disease outbreaks across public health system databases. In the first fusion level, collected data is used to detect and track indicative bio-events using latent semantic analysis and unsupervised clustering. In the second fusion level, clusters produced via the first are used to feed dynamic...
Decentralized multisensor-multitarget tracking has numerous advantages over single-sensor or single-platform tracking. In this paper, we present a solution to one of the main problems of decentralized tracking, namely, distributed information transfer and fusion among the participating platforms. This paper presents a hierarchial multi-level decision mechanism for collaborative distributed data fusion...
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