• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제6권6호
• /
• pp.1496-1521
• /
• 2012

Uncertainty is ubiquitous in target tracking wireless sensor networks due to environmental noise, randomness of target mobility and other factors. Sensing results are always unreliable. This paper considers unreliability as it occurs in wireless sensor networks and its impact on target-tracking accuracy. Firstly, we map intersection pairwise sensors' uncertain boundaries, which divides the monitor area into faces. Each face has a unique signature vector. For each target localization, a sampling vector is built after multiple grouping samplings determine whether the RSS (Received Signal Strength) for a pairwise nodes' is ordinal or flipped. A Fault-Tolerant Target-Tracking (FTTT) strategy is proposed, which transforms the tracking problem into a vector matching process that increases the tracking flexibility and accuracy while reducing the influence of in-the-filed factors. In addition, a heuristic matching algorithm is introduced to reduce the computational complexity. The fault tolerance of FTTT is also discussed. An extension of FTTT is then proposed by quantifying the pairwise uncertainty to further enhance robustness. Results show FTTT is more flexible, more robust and more accurate than parallel approaches.

• 대한원격탐사학회지
• /
• 제23권5호
• /
• pp.421-430
• /
• 2007

This paper presents the results of the ocean surface current velocity estimation using 6 Radarsat-1 SAR images acquired in west coastal area near Incheon. We extracted the surface velocity from SAR images based on the Doppler shift approach in which the azimuth frequency shift is related to the motion of surface target in the radar direction. The Doppler shift was measured by the difference between the Doppler centroid estimated in the range-compressed, azimuth-frequency domain and the nominal Doppler centroid used during the SAR focusing process. The extracted SAR current velocities were statistically compared with the current velocities from the high frequency(HF) radar in terms of averages, standard deviations, and root mean square errors. The problem of the unreliable nominal Doppler centroid for the estimation of the SAR current velocity was corrected by subtracting the difference of averages between SAR and HF-radar current velocities from the SAR current velocity. The corrected SAR current velocity inherits the average of HF-radar data while maintaining high-resolution nature of the original SAR data.

• 대한원격탐사학회지
• /
• 제34권1호
• /
• pp.141-150
• /
• 2018

Crop type classification is essential for supporting agricultural decisions and resource monitoring. Remote sensing techniques, especially using hyperspectral imagery, have been effective in agricultural applications. Hyperspectral imagery acquires contiguous and narrow spectral bands in a wide range. However, large dimensionality results in unreliable estimates of classifiers and high computational burdens. Therefore, reducing the dimensionality of hyperspectral imagery is necessary. In this study, the Random Forest (RF) classifier was utilized for dimensionality reduction as well as classification purpose. RF is an ensemble-learning algorithm created based on the Classification and Regression Tree (CART), which has gained attention due to its high classification accuracy and fast processing speed. The RF performance for crop classification with airborne hyperspectral imagery was assessed. The study area was the cultivated area in Chogye-myeon, Habcheon-gun, Gyeongsangnam-do, South Korea, where the main crops are garlic, onion, and wheat. Parameter optimization was conducted to maximize the classification accuracy. Then, the dimensionality reduction was conducted based on RF variable importance. The result shows that using the selected bands presents an excellent classification accuracy without using whole datasets. Moreover, a majority of selected bands are concentrated on visible (VIS) region, especially region related to chlorophyll content. Therefore, it can be inferred that the phenological status after the mature stage influences red-edge spectral reflectance.

• 대한원격탐사학회지
• /
• 제19권1호
• /
• pp.61-70
• /
• 2003

This paper proposes an autonomous approach to localize the center of fiducial marks included in aerial photographs without precise geometric information and human interactions. For this localization, we present a conceptual model based on two assumptions representing symmetric characteristics of fiducial area and fiducial mark. The model makes it possible to locate exact center of a fiducial mark by checking the symmetric characteristics of pixel value distribution around the mark. The proposed approach is composed of three steps: (a) determining the symmetric center of fiducial area, (b) finding the center of a fiducial mark with unit pixel accuracy, and finally (c) localizing the exact center up to sub-pixel accuracy. The symmetric center of the mark is calculated tv successively applying three geometric filters: simplified ${\nabla}^2$G (Laplacian of Gaussian) filter, symmetry enhancement filter, and high pass filter. By introducing a self-diagnosis function based on the self-similarity measurement, a way of rejecting unreliable cases of center calculation is proposed, as well. The experiments were done with respect to 284 samples of fiducial marks composed of RMK- and RC-style ones extracted from 51 scanned aerial photographs. It was evaluated in the visual inspection that the proposed approach had resulted the erroneous identification with respect to only one mark. Although the proposed approach is based on weak constraints, being free from the exact geometric model of the fiducial marks, experimental results showed that the proposed approach is sufficiently robust and reliable.

• International Journal of Control, Automation, and Systems
• /
• 제2권4호
• /
• pp.485-493
• /
• 2004

Open-loop position estimation methods are commonly used in mobile robot applications. Their strength lies in the speed and simplicity with which an estimated position is determined. However, these methods can lead to inaccurate or unreliable estimates. Two position estimation methods are developed in this paper, one using a single optical flow sensor and a second using two optical sensors. The first method can accurately estimate position under ideal conditions and also when wheel slip perpendicular to the axis of the wheel occurs. The second method can accurately estimate position even when wheel slip parallel to the axis of the wheel occurs. Location of the sensors is investigated in order to minimize errors caused by inaccurate sensor readings. Finally, a method is implemented and tested using a potential field based navigation scheme. Estimates of position were found to be as accurate as dead-reckoning in ideal conditions and much more accurate in cases where wheel slip occurs.

• 한국정보과학회논문지:정보통신
• /
• 제36권4호
• /
• pp.339-350
• /
• 2009

무선 센서 네트워크에서 센서 노드의 한정된 배터리 자원은 네트워크 수명에 직접적인 영향을 끼친다. 따라서 불필요한 전력 소모를 줄이기 위해, 많은 경우 최소한의 센서 노드만을 활성 모드로 유지하고 나머지는 휴면 모드로 유지한다. 그러나 이러한 경우, 예상하지 못한 결함으로 인해 센서 노드가 감지 및 전송 기능을 수행하지 못하게 되면 네트워크 서비스를 안정적으로 제공할 수가 없다. 따라서 센서노드의 결함에도 불구하고 감지수준을 일정하게 유지하는 것은 신뢰성 있는 감지환경을 제공하는 데 있어 매우 중요하다. 본 논문에서는 센서 노드의 결함으로 인한 감지수준 저하의 문제를 효과적으로 극복하기 위해 FCP(Fault-tolerant Coverage Preserving) 기법을 제안한다. FCP 기법에서는 각 활성 노드에 대해 백업 노드 집합을 미리 선정하여, 활성 노드의 결함 시 결함 노드를 대신하도록 한다. 성능 평가 결과, FCP 기법이 기존 결함 허용 기법들에 비해 평균 87.2% 향상된 감지범위 보존 성능을 보일 뿐 아니라, 추가 백업 노드 수와 추가 제어 메시지 전송량 측면에서도 각각 평균 57.6%, 평균 99.5% 향상된 효율성을 제공함을 보였다.

• 한국농공학회논문집
• /
• 제53권6호
• /
• pp.7-16
• /
• 2011

This study discussed the applicability of satellite SAR (Synthetic Aperture Radar) imagery with regard to reservoir monitoring, and tried the extraction of reservoir storage from multi-temporal C-band RADARSAT-1 SAR backscattering images of Yedang and Goongpyeong agricultural reservoirs, acquired from May to October 2005. SAR technology has been advanced as a complementary and alternative approach to optical remote sensing and in-situ measurement. Water bodies in SAR imagery represent low brightness induced by low backscattering, and reservoir storage can be derived from the backscatter contrast with the level-area-volume relationship of each reservoir. The threshold segmentation over the routine preprocessing of SAR images such as speckle reduction and low-pass filtering concluded a significant correlation between the SAR-derived reservoir storage and the observation record in spite of the considerable disagreement. The result showed up critical limitations for adopting SAR data to reservoir monitoring as follows: the inappropriate specifications of SAR data, the unreliable rating curve of reservoir, the lack of climatic information such as wind and precipitation, the interruption of inside and neighboring land cover, and so on. Furthermore, better accuracy of SAR-based reservoir monitoring could be expected through different alternatives such as multi-sensor image fusion, water level measurement with altimeters or interferometry, etc.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
• /
• pp.816-819
• /
• 2006

One of the most difficult parameters to measure in the sea is current speed and direction. Recently, efforts are being made to estimate the ocean current vectors by utilizing sequential satellite imageries. In this study, we attempted to estimated sea surface current vector (sscv) by using satellite ocean color imageries of SeaWifs around the Korean Peninsula. This ocean color image data has 1-day sampling interval and spatial resolution of 1x1 km. Maximum cross-correlation method is employed which is aimed to detect similar patterns between sequential images. The estimated current vectors are compared to the surface geostrophic current vectors obtained from altimeter of sea level height data. In utilizing the color imagery data, some limitations and drawbacks exist so that in warm water region where phytoplankton concentration is relatively lower than in cold water region, estimation of sscv is poor and unreliable. On the other hand, two current vector fields agree reasonably well in the Korean South Sea region where high concentration of chlorophyll-a and weak tide is observed. In the future, with ocean color images of shorter sampling interval by COMS satellite, the algorithm and methodology developed in the study would be useful in providing the information for the ocean current around Korean Peninsula.

• 제어로봇시스템학회논문지
• /
• 제13권3호
• /
• pp.230-234
• /
• 2007

Generally, huge amounts of data traffic are generated by using broadcasting method to deliver sensing data to a sink node reliably so that it makes a severe network saturation problem resulting in unreliable data transfer. In order to handle this problem, a new congestion control protocol is required for supporting reliable data transfer, minimal use of energy and network resources at the same time in wireless sensor networks. In this paper, it proposes a Protocol to guarantee both a reliable transfer in data accuracy and minimum consumption of energy waste by using Hop-by-Hop sequence number and DSbACK(Delayed and Selective ACK Buffer Condition) scheme. In addition, it proves that reliability and energy efficiency are enhanced by the proposed method with the simulation results performed on TinyOS platform which is a component based built-in OS announced by UC Berkely with the performance comparison of other existing methods.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
• /
• pp.357-360
• /
• 2007

An asset tracking using wireless sensor network is concerned with geographical locations of sensor nodes. The limited size of sensor nodes makes them attractable for tracking service, at the same time their size causes power restrictions, limited computation power, and storage restrictions. Due to such constrained capabilities, the wireless sensor network basically assumes the failure of sensor nodes. This causes a set of concerns in designing asset tracking system on wireless sensor network and one of the most critical factors is location uncertainty of sensor nodes. In this paper, we classify the location uncertainty problem in asset tracking system into following cases. First, sensor node isn't read at all because of sensor node failure, leading to misunderstanding that asset is not present. Second, incorrect location is read due to interference of RSSI, providing unreliable location of asset. We implemented and installed our asset tracking system in a real environment and continuously monitored the status of asset and measured error rate of location of sensor nodes. We present experimental results that demonstrate the location uncertainty problem in asset tracking system using wireless sensor network.