• ETRI Journal
• /
• v.37 no.3
• /
• pp.533-540
• /
• 2015

In wireless localization, several linear closed-form solution (LCS) methods have been investigated as a direct result of the drawbacks that plague the existing iterative methods, such as the local minimum problem and heavy computational burden. Among the known LCS methods, both the direct solution method and the difference of squared range measurements method are considered in this paper. These LCS methods do not have any of the aforementioned problems that occur in the existing iterative methods. However, each LCS method does have its own individual error property. In this paper, a hybrid LCS method is presented to reduce these errors. The hybrid LCS method integrates the two aforementioned LCS methods by using two check points that give important information on the probability of occurrence of each LCS's individual error. The results of several Monte Carlo simulations show that the proposed method has a good performance. The solutions provided by the proposed method are accurate and reliable. The solutions do not have serious errors such as those that occur in the conventional standalone LCS and iterative methods.

• Journal of Institute of Control, Robotics and Systems
• /
• v.19 no.7
• /
• pp.633-639
• /
• 2013

Several estimation methods used in the range measurement based wireless localization area have individual problems. These problems may not occur according to certain application areas. However, these problems may give rise to serious problems in particular applications. In this paper, three methods, ILS (Iterative Least Squares), DS (Direct Solution), and DSRM (Difference of Squared Range Measurements) methods are considered. Problems that can occur in these methods are defined and a simple hybrid solution is presented to solve them. The ILS method is the most frequently used method in wireless localization and has local minimum problems and a large computational burden compared with closed-form solutions. The DS method requires less processing time than the ILS method. However, a solution for this method may include a complex number caused by the relations between the location of reference nodes and range measurement errors. In the near-field region of the complex solution, large estimation errors occur. In the DSRM method, large measurement errors occur when the mobile node is far from the reference nodes due to the combination of range measurement error and range data. This creates the problem of large localization errors. In this paper, these problems are defined and a hybrid localization method is presented to avoid them by integrating the DS and DSRM methods. The defined problems are confirmed and the performance of the presented method is verified by a Monte-Carlo simulation.

• Korean Journal of Remote Sensing
• /
• v.32 no.2
• /
• pp.73-86
• /
• 2016

In this study, an algorithm to estimate Aerosol Optical Thickness (AOT) over small cities during nighttime has been developed by using the radiance from artificial light sources in small cities measured from Visible Infrared Imaging Radiometer Suite (VIIRS) sensor's Day/Night Band (DNB) aboard the Suomi-National Polar Partnership (Suomi-NPP) satellite. The algorithm is based on Beer's extinction law with the light sources from the artificial lights over small cities. AOT is retrieved for cloud-free pixels over individual cities, and cloud-screening was conducted by using the measurements from M-bands of VIIRS at infrared wavelengths. The retrieved nighttime AOT is compared with the aerosol products from MODerate resolution Imaging Spectroradiometer (MODIS) aboard Terra and Aqua satellites. As a result, the correlation coefficients over individual cities range from around 0.6 and 0.7 between the retrieved nighttime AOT and MODIS AOT with Root-Mean-Squared Difference (RMSD) ranged from 0.14 to 0.18. In addition, sensitivity tests were conducted for the factors affecting the nighttime AOT to estimate the range of uncertainty in the nighttime AOT retrievals. The results of this study indicate that it is promising to infer AOT using the DNB measaurements over small cities in Korea at night. After further development and refinement in the future, the developed retrieval algorithm is expected to produce nighttime aerosol information which is not operationally available over Korea.