S. N. Karimah, M. R. K. Aziz and T. Matsumoto, "A PTDOA-DRSS hybrid factor graph-based unknown radio wave geolocation," 2018 International Conference on Signals and Systems (ICSigSys), Bali, 2018, pp. 281-288, https://doi.org/10.1109/ICSIGSYS.2018.8372773
A PTDOA-DRSS hybrid factor graph-based unknown radio wave geolocation
|Author:||Karimah, Shofiyati Nur1; Aziz, Muhammad Reza Kahar2; Matsumoto, Tad1,3|
1Japan Advanced Institute of Science and Technology (JAIST), 1-1 Asahidai, Nomi, Ishikawa, 923-1292 JAPAN
2Electrical Engineering, Institut Teknologi Sumatera (ITERA), Lampung Selatan, 35365 INDONESIA
3Centre for Wireless Communications, University of Oulu, Oulu, 90014 FINLAND
|Online Access:||PDF Full Text (PDF, 1.3 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2020042422317
Institute of Electrical and Electronics Engineers,
|Publish Date:|| 2020-04-24
We propose a hybrid Pythagorean Time Difference of Arrival and Differential Received Signal Strength based Factor Graph (PTDOA-DRSS-FG) to estimate the location of unknown radio wave emitter in outdoor environments. The term of “unknown” indicates that the knowledge of neither time of departure (TOD) nor absolute transmit power of the radio wave emitter are required. The PTDOA-FG can eliminate the necessity of TOD knowledge of the target signal transmission and DRSS-FG can eliminate the necessity of the knowledge of target absolute transmit power. However, PTDOA-FG alone requires perfect time synchronism between sensors, which is difficult in practice. On the other hand, DRSS-FG alone requires the most suitable monitoring spots. In this paper, PTDOA-FG is used to provide the rough estimation of the target position to select the most suitable monitoring spots for DRSS-FG technique. It is shown that, in terms of root mean square error (RMSE) vs. iteration times, the achieved RMSE of the proposed technique is better than the PTDOA-FG alone and very close to the DRSS reference, i.e., the DRSS-FG technique with the idealistic monitoring spots. Performing the proposed technique in the framework of factor graph (FG) does not require excessive computational complexity due to the fact that using the Gaussian distribution model, it uses mean and variance only with the sum-product algorithm.
|Pages:||281 - 288|
International Conference on Signals and Systems
|Type of Publication:||
A4 Article in conference proceedings
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
This research, in part, supported by Beasiswa Unggulan Kementrian Pendidikan dan Kebudayaan Indonesia, in part, Kiban (B) No.15H04007, in part, JAIST Core-to-Core Program, and in part, by Koden Electronics Co., Ltd. Authors are very grateful for their support.
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