Cherntanomwong, Panarat

Loading...
Thumbnail Image
Preferred name
Cherntanomwong, Panarat
Main Affiliation
Email
panarat.ch@kmitl.ac.th

Settings

Now showing 1 - 3 of 3
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Soft-clustering technique for fingerprint-based localization
    (2018-01-01)
    Cherntanomwong, Panarat
    ;
    Sooraksa, Pitikhate
    In this paper, the soft-clustering algorithm for the fingerprint-based localization technique is proposed. In an indoor environment, the fingerprint-based localization technique is usually employed since it can deal with signal fluctuation. Its basic principle is to find the target location by comparing its signal parameters with a previously recorded database of knownlocation- signal parameters. Here, the received signal strength indicator (RSSI) provided by the wireless sensor network (WSN) is used as the signal parameter. The high accuracy of location estimation requires a very fine spatial resolution of the database, corresponding to the time consumed for pattern matching. To reduce the calculation time, clustering can be applied because it can reduce the database size by grouping similar data in the same cluster. The accuracy of the algorithm to cluster the target location and fingerprint locations is the main concern. The result shows that the clustering technique used can successfully cluster the target sensing node into an appropriate cluster. This implies that, by using soft clustering with the fingerprint technique, the target location can be estimated faster than by using classical fingerprint techniques since the target location can be estimated within a small set of fingerprints in the cluster, not with all fingerprints in the database.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Signal subspace interpolation from discrete measurement samples In constructing a database for location fingerprint technique
    (2009-01-01)
    Cherntanomwong, Panarat
    ;
    Takada, Jun Ichi
    ;
    Tsuji, Hiroyuki
    In this paper, a method of the signal subspace interpolation to constructing a continuous fingerprint database for radio localization is proposed. When using the fingerprint technique, enhancing the accuracy of location estimation requires very fine spatial resolution of the database, which entails much time in collecting the data to build up the database. Interpolated signal subspace is presented to achieve a fine spatial resolution of the fingerprint database. The angle of arrival (AOA) and the measured signal subspace at known locations are needed to obtain the interpolated signal subspaces. The effectiveness of this method is verified by an outdoor experiment and the estimated location using this method was compared with those using the geometrically calculated fingerprint and the measured signal subspace fingerprint techniques. Copyright © 2009 The Institute of Electronics, Information and Communication Engineers.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    RFID based localization techniques for indoor environment
    (2010-05-24)
    Pathanawongthum, Nichapat
    ;
    Cherntanomwong, Panarat
    In this paper, the Radio Frequency Identification (RFID) technology is used for indoor localization (i.e. location estimation). The location of a RFID reader is estimated based on the known locations of the RFID tags attached to the ceiling with 60 cm separation. Two arranged pattern of tags are considered. One is a square arranged pattern and another one is a triangle arranged pattern. Then, two simple location estimation methods are employed. The basic principle of location estimation for both methods is based on the average of the locations of detected tags observed by the reader. For the first estimation method, only maximum and minimum coordinates of detected tag are average. But for the second estimation method, all coordinates of detected tag are average. The effectiveness of tag arranged pattern and the location estimation methods is evaluated by the indoor experiment data. The results of the location estimated by both methods are compared. Also, the results of location estimation using the square and triangle arranged patterns are also shown. It is illustrated that the triangle arranged patterns gives better results than the square pattern in some certain. Moreover, the location estimations error for all observed locations for both methods are less than 30 cm. Furthermore, the average of the location estimation error for both methods is less than 15 cm. This is satisfied and applicable for some indoor applications.