• 한국음향학회지
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• 제23권5호
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• pp.410-419
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• 2004

본 논문에서는 베이시안에 기반한 신뢰도 융합 기법을 제안한다. 음성인식에서 신뢰도는 인식 결과에 대한 신뢰의 정도를 말하며, 인식 결과가 맞는 지의 여부를 판단할 수 있다. 개별 신뢰도 기법의 신뢰도 값을 융합하여 최종 판단을 내리는 집중형 융합 방식과 개별 신뢰도 기법의 판단 결과들을 융합하는 분산형 융합의 두 가지 방식에 대해 최적의 베이시안 융합규칙이 제시되었다. 고립단어 인식에서의 미등록어 거절 실험 결과 집중형 베이시안 신뢰도 융합 기법은 개별 신뢰도 기법에 비해 13% 이상의 상대적인 에러 감소 효과를 보였으나, 분산형 베이시안 융합은 성능의 향상을 보이지 못했다.

• International Journal of Control, Automation, and Systems
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• 제1권4호
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• pp.444-452
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• 2003

An integration system with multi-measurement sets can be realized via combined application of a centralized and federated Kalman filter. It is difficult for the centralized Kalman filter to remove a failed sensor in comparison with the federated Kalman filter. All varieties of Kalman filters monitor innovation sequence (residual) for detection and isolation of a failed sensor. The innovation sequence, which is selected as an indicator of real time estimation error plays an important role in adaptive mechanism design. In this study, the centralized Kalman filter with adaptive measurement fusion is introduced by means of innovation sequence. The objectives of adaptive measurement fusion are automatic isolation and recovery of some sensor failures as well as inherent monitoring capability. The proposed adaptive filter is applied to the GPS/SDINS integration system with an additional sensor. Simulation studies attest that the proposed adaptive scheme is effective for isolation and recovery of immediate sensor failures.

• International Journal of Control, Automation, and Systems
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• 제4권2호
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• pp.165-171
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• 2006

This paper proposes a data fusion algorithm of nonlinear multi sensor dynamic systems of synchronous sampling based on filtering step by step. Firstly, the object state variable at the next time index can be predicted by the previous global information with the systems, then the predicted estimation can be updated in turn by use of the extended Kalman filter when all of the observations aiming at the target state variable arrive. Finally a fusion estimation of the object state variable is obtained based on the system global information. Synchronously, we formulate the new algorithm and compare its performances with those of the traditional nonlinear centralized and distributed data fusion algorithms by the indexes that include the computational complexity, data communicational burden, time delay and estimation accuracy, etc.. These compared results indicate that the performance from the new algorithm is superior to the performances from the two traditional nonlinear data fusion algorithms.

• 한국항공우주학회지
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• 제38권10호
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• pp.1012-1019
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• 2010

본 논문에서는 다중표적 비행시험을 위한 비행 자료처리 시스템이 설계되었다. 비행자료 처리를 위해 표적그룹 처리, 자료융합 처리 및 자료연동 처리가 수행 되었으며, 자료융합 필터로서 집중형 칼만필터와 연합형 칼만필터를 설계하였다. 특히 집중형 필터에 레이더의 SNR과 추정기법을 적용하여 비행체의 저고도 계측을 개선하였다. 개발된 시스템을 다중표적 비행시험에 적용한 결과, 저고도 및 초기구간에서 개선된 비행궤적을 확인할 수 있었다.

• 한국항공운항학회지
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• 제24권2호
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• pp.1-10
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• 2016

A GPS/SDINS/ST(Star Tracker) integrated sensor algorithm is more robust than the GPS/SDINS and the ST/SDINS systems on exploration of other planets. Most of the advanced studies shown that GPS/SDINS/ST integrated sensor with centralized Kalman filter was more accurate than those 2 integrated systems. The system, however, consist of a single filter, it is vulnerable to defects on failed data. To improve the problem, we work out a study using federated Kalman filter(No-Reset mode) and centralized Kalman filter with adaptive measurement fusion which known as robustness on fault. The simulation results show that the debasing influences are reduced and the computation is enable at least 100Hz. Further researches that the initial calibration in accordance with observability and applying the exploration trajectory are needed.

• 센서학회지
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• 제25권6호
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• pp.418-422
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• 2016

A filtering algorithm based on the decentralized moving average Kalman filter with uncertainties is proposed in this paper. The proposed filtering algorithm presented combines the Kalman filter with the moving average strategy. A decentralized fusion algorithm with the weighted sum structure is applied to the local moving average Kalman filters (LMAKFs) of different window lengths. The proposed algorithm has a parallel structure and allows parallel processing of observations. Hence, it is more reliable than the centralized algorithm when some sensors become faulty. Moreover, the choice of the moving average strategy makes the proposed algorithm robust against linear discrete-time dynamic model uncertainties. The derivation of the error cross-covariances between the LMAKFs is the key idea of studied. The application of the proposed decentralized fusion filter to dynamic systems within a multisensor environment demonstrates its high accuracy and computational efficiency.

• 한국항해항만학회지
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• 제28권7호
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• pp.635-640
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• 2004

In this paper, a tracking algorithm for autonomous navigation of automated guided vehicles (AGVs) operating in container terminals is presented. The developed navigation algorithm takes the form of a federated information filter used to detect other AGVs and avoid obstacles using fused information from multiple sensors. Being equivalent to the Kalman filter (KF) algebraically, the information filter is extended to N-sensor distributed dynamic systems. In multi-sensor environments, the information-based filter is easier to decentralize, initialize, and fuse than a KF-based filter. It is proved that the information state and the information matrix of the suggested filter, which are weighted in terms of an information sharing factor, are equal to those of a centralized information filter under the regular conditions. Numerical examples using Monte Carlo simulation are provided to compare the centralized information filter and the proposed one.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권1호
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• pp.229-240
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• 2012

Advances in MEMS and CMOS technologies have motivated the development of low cost/power sensors and wireless multimedia sensor networks (WMSN). The WMSNs were created to ubiquitously harvest multimedia content. Such networks have allowed researchers and engineers to glimpse at new Machine-to-Machine (M2M) Systems, such as remote monitoring of biosignals for telemedicine networks. These systems require the acquisition of a large number of data streams that are simultaneously generated by multiple distributed devices. This paradigm of data generation and transmission is known as event-streaming. In order to be useful to the application, the collected data requires a preprocessing called data fusion, which entails the temporal alignment task of multimedia data. A practical way to perform this task is in a centralized manner, assuming that the network nodes only function as collector entities. However, by following this scheme, a considerable amount of redundant information is transmitted to the central entity. To decrease such redundancy, data fusion must be performed in a collaborative way. In this paper, we propose a collaborative data alignment approach for event-streaming. Our approach identifies temporal relationships by translating temporal dependencies based on a timeline to causal dependencies of the media involved.

• 한국항행학회논문지
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• 제18권1호
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• pp.29-34
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• 2014

데이터 융합 기술은 단일 독립 레이더에 의해 이루어지는 것보다 더 정확한 추정치들을 갖기 위해 다중 레이더와 관련 정보로부터 데이터를 결합한다. 본 논문에서는 다중 레이더에서 처리되는 패킷의 지연 시간 및 손실을 분석하여 다중 레이더 데이터 융합시 중앙 자료처리 연산부에서 자료 처리 인터벌을 최소화한다. 이를 위하여 중앙 집중형 자료융합에 대한 레이더 네트워크를 모델링하고, NS-2를 이용하여 각각의 큐를 M/M/1/K로 가정하고 큐 내부에서의 패킷 지연시간과 패킷 손실을 분석한다. 분석 자료를 통해 다중 레이더 자료를 융합처리 할 때 평균 지연시간을 확인 하였으며, 이 지연시간은 융합센터에서의 레이더 자료 대기시간 기준으로 사용될 수 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제4권6호
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• pp.1042-1062
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• 2010

Cooperative spectrum sensing (CSS) is an effective technology for alleviating the unreliability of local spectrum sensing due to fading/shadowing effects. Unlike most existing solutions, this paper considers the use of CSS technology in decentralized networks where a fusion center is not available. In such a decentralized network, some attackers may sneak into the ranks of cooperative users. On the basis of recent advances in bio-inspired consensus algorithms, an attack-proof, decentralized CSS scheme is proposed in which all secondary users can maintain cooperative sensing by exchanging information locally instead of requiring centralized control or data fusion. Users no longer need any prior knowledge of the network. To counter three potential categories of spectrum sensing data falsification (SSDF) attacks, some anti-attack strategies are applied to the iterative process of information exchange. This enables most authentic users to exclude potentially malicious users from their neighborhood. As represented by simulation results, the proposed scheme can generally ensure that most authentic users reach a consensus within the given number of iterations, and it also demonstrates much better robustness against different SSDF attacks than several existing schemes.