• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.5C
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• pp.355-364
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• 2012

Target processing mechanisms are necessary to collect target information, real-time data fusion, and tactical environment recognition for cooperative engagement ability. Among these mechanisms, the target tracking starts from predicting state of speed, acceleration, and location by using sensors' measurements. However, it can be a problem to give the reliability because the measurements have a certain uncertainty. Thus, a technique which uses multiple sensors is needed to detect the target and increase the reliability. Also, data fusion technique is necessary to process the data which is provided from heterogeneous sensors for target tracking. In this paper, a target tracking algorithm is proposed based on probabilistic data association(PDA) by fusing radar and ESM sensor measurements. The radar sensor's azimuth and range measurements and the ESM sensor's bearing-only measurement are associated by the measurement fusion method. After gating associated measurements, state estimation of the target is performed by PDA filter. The simulation results show that the proposed algorithm provides improved estimation under linear and circular target motions.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.973-975
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• 2016

In this paper, we propose a selective extended Kalman filter based accurate pose estimation of the rigid body using a sensor fusion method. The pose of a rigid body can be estimated roughly by the Gauss-Newton method using the acceleration data and geomagnetic data, which can be refined with vision information and the gyro sensor information. However strong external interference noise makes the rough pose estimation difficult. In this paper, according to the measurement level of the external interference noise, the extended Kalman filter selectively uses mostly vision and gyro sensor information to increase the estimation credibility under strong interference noise environment.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.2
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• pp.106-114
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• 2017

In this paper, we propose the method of designing an extended kalman filter in order to accurately measure the position of the spatial-phase system using sensor fusion. We use the quaternion as a state variable in expressing the attitude of an object. Then, the attitude of rigid body can be calculated from the accelerometer and magnetometer by applying the Gauss-Newton method. We estimate the changes of state by using the measurements obtained from the gyroscope, the quaternion, and the vision informations by ARVR_SDK. To increase the accuracy of estimation, we designed and implemented the extended kalman filter, which showed excellent ability to adjust and compensate the sensor error. As a result, we could experimentally demonstrate that the reliability of the attitude estimation value can be significantly increased.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.6
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• pp.1391-1396
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• 2011

A way to increase productivity in agriculture that is labor-centered industry is to graft IT technology. Today, many technologies in ubiquitous computing are deployed in all areas of society such as traffic control, automotive manufacturing, construction, defence, healthcare and clinical services. These IT technologies is gaining more attention as a fusion technology among traditional industries. To successfully build ubiquitous agriculture environment, it needs optimized core technology development for agriculture that includes sensor node H/W, middleware platform, routing protocol and agriculture environment application services. To achieve accurate botany growth environment management, we propose a green growth environment management system using environmental factor monitoring sensor and biological information sensors in greenhouse. By using our proposed system, it is expected to realize fusion complex agriculture technology with low cost.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.12
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• pp.265-274
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• 2012

In this paper, we propose a method for preceding vehicle detection and tracking with motion estimation by radar-vision sensor fusion. The motion estimation proposed results in not only correction of inaccurate lateral position error observed on a radar target, but also adaptive detection and tracking of a preceding vehicle by compensating the changes in the geometric relation between the ego-vehicle and the ground due to the driving. Furthermore, the feature-based motion estimation employed to lessen computational burden reduces the number of deployment of the vehicle validation procedure. Experimental results prove that the correction by the proposed motion estimation improves the performance of the vehicle detection and makes the tracking accurate with high temporal consistency under various road conditions.

• Annual Conference of KIPS
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• 2009.04a
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• pp.1260-1263
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• 2009

제한된 배터리를 가지는 센서 네트워크의 수명을 길게 하기 위하여 에너지 소비를 줄이고 효율성을 높이는 다양한 방법이 제안되었다. 센서 노드에서의 데이터 전송은 가장 큰 에너지 소비 활동이 되기 때문에, 데이터가 전송되는 양을 줄여서 에너지 소비를 줄일 수 있는 방법이 한 부분으로 연구되고 있다. 본 논문에서는 이와 같은 특징을 반영하고, 시간적 연관성만을 고려한 데이터 퓨전 기법인 TiNA(Temporal coherency-aware in-Network Aggregation)를 기반으로 시간, 공간적 연관성을 동시에 고려하여 데이터 퓨전을 하는 효율적인 데이터 퓨전(Data Fusion) 기법을 제안하였다.

• Journal of information and communication convergence engineering
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• v.13 no.3
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• pp.152-158
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• 2015

We consider the problem of designing independently operating local quantizers at nodes in distributed estimation systems, where many spatially distributed sensor nodes measure a parameter of interest, quantize these measurements, and send the quantized data to a fusion node, which conducts the parameter estimation. Motivated by the discussion that the estimation accuracy can be improved by using the quantized data with a high probability of occurrence, we propose an iterative algorithm with a simple design rule that produces quantizers by searching boundary values with an increased likelihood. We prove that this design rule generates a considerably reduced interval for finding the next boundary values, yielding a low design complexity. We demonstrate through extensive simulations that the proposed algorithm achieves a significant performance gain with respect to traditional quantizer designs. A comparison with the recently published novel algorithms further illustrates the benefit of the proposed technique in terms of performance and design complexity.

• Proceedings of the Korean Information Science Society Conference
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• 2007.06b
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• pp.437-440
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• 2007

최근 환경 문제를 해결하기 위하여 환경 문제의 많은 컴퓨터 기술들이 응용되고 있다. 환경 정보는 환경오염원 및 주위에 미치는 영향과 오염된 농도에 대한 정보를 연구 및 분석 할 수 있는 분야이다. 최근 환경에 관련 연구가 일부에서 수행되고 있으나 이를 IT기술과 접목하여 다양한 정보를 효율적으로 저장 및 검색 할 수 있는 시스템은 부족한 실정이다. 또한 현재 환경오염의 측정방법으로는 수작업으로 이루어지는 경우가 많아서 공간적 및 물리적 제약이 있는 따르는 실정이다. 환경오염에 관한 정보를 센서를 사용하여 사용자에게 실시간으로 효과적으로 저장 관리하여 관련된 연구자들 간에 서로가 필요한 정보를 쉽게 공유할 수 있도록 본 논문에서는 Ubiquitous Sensor Network(USN), Java Message Service(JMS) 및 Webservice를 이용한 환경 모니터링 서비스를 제안 한다. 본 논문에서 제안한 시스템은 환경정보와 사용자간에 유연성, 확장성 및 실시간을 보장해 주는 시스템을 구현한다.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.400-406
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• 2002

Recently, the enormous increase in the volume of remotely sensed data is being acquired by an ever-growing number of earth observation satellites. The combining of diversely sourced imagery together is an important requirement in many applications such as data fusion, city modeling and object recognition. Aerial triangulation is a procedure to reconstruct object space from imagery. However, since the different kinds of imagery have their own sensor model, characteristics, and resolution, the previous approach in aerial triangulation (or georeferencing) is performed on a sensor model separately. This study evaluated the advantages of aerial triangulation of large number of images from multi-sensors simultaneously. The incorporated multi-sensors are frame, push broom, and whisky broom cameras. The limits and problems of push-broom or whisky broom sensor models can be compensated by combined triangulation with frame imagery and vise versa. The reconstructed object space from multi-sensor triangulation is more accurate than that from a single model. Experiments conducted in this study show the more accurately reconstructed object space from multi-sensor triangulation.

• Korean Journal of Remote Sensing
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• v.19 no.3
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• pp.255-261
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• 2003

Recently, the enormous increase in the volume of remotely sensed data is being acquired by an ever-growing number of earth observation satellites. The combining of diversely sourced imagery together is an important requirement in many applications such as data fusion, city modeling and object recognition. Aerial triangulation is a procedure to reconstruct object space from imagery. However, since the different kinds of imagery have their own sensor model, characteristics, and resolution, the previous approach in aerial triangulation (or georeferencing) is purformed on a sensor model separately. This study evaluated the advantages of aerial triangulation of large number of images from multi-sensors simultaneously. The incorporated multi-sensors are frame, push broom, and whisky broom cameras. The limits and problems of push-broom or whisky broom sensor models can be compensated by combined triangulation with other sensors The reconstructed object space from multi-sensor triangulation is more accurate than that from a single model. Experiments conducted in this study show the more accurately reconstructed object space from multi-sensor triangulation.