Adaptive filtration of radio source movement parameters with complex use of sensor network data based on TDOA and RSS methods
Keywords:radio source, unmanned aerial vehicle, UAV, adaptive algorithm, statistical simulation, sensor network, quasi-optimal algorithm, feedback, time-difference of arrival, TDOA, received signal strength, RSS, WSN
AbstractThe optimal and quasi-optimal adaptive algorithms for filtration of parameters of radio source movement with different kinds of maneuvers have been synthesized on the basis of mathematical tools of discrete-time mixed Markov processes. These algorithms involve the complex use of sensor network data obtained on the basis of the TDOA and RSS methods. The devices implementing the above algorithms are multichannel and belong to the class of devices with feedbacks between channels. The presence of feedbacks between channels is stipulated by the Markov property of discrete component describing types of radio source movement. In the quasi-optimal adaptive algorithm, the processing of measurement values coming from sensors of the sensor network is performed by using the sequential calculation procedure. At the same time, this algorithm ensures polygaussian approximation of a posteriori probability density of the estimated vector of parameters of radio source movement. The analysis of quasi-optimal algorithm is carried out by employing the computer-aided statistical simulation using an example of estimating the movement parameters of UAV performing different kinds of maneuvers and sending out radio waves.
BASKAKOV, S.S. Study of methods to improve efficiency of virtual coordinate routing in wireless sensor networks. Vestnik MGTU. Insrtument Engineering, n.2, p.112-124, 2009. URI: http://vestnikprib.ru/eng/catalog/it/hidden/197.html.
WALLACE, R.J.; LOFFI, J.M. Examining unmanned aerial system threats & defenses: A conceptual analysis. Int. J. Aviation, Aeronautics, and Aerospace, v.2, n.4, 2015. DOI: https://doi.org/10.15394/ijaaa.2015.1084.
Sky is no limit for your security. URI: http://dronebouncer.com/.
EL GEMAYEL, Noha; KOSLOWSKI, Sebastian; JONDRAL, Friedrich K.; TSCHAN, Joachim. A low cost TDOA localization system: Setup, challenges and results. Proc. of 10th Workshop on Positioning Navigation and Communication, WPNC, 20-21 May 2013, Dresden, Germany. IEEE, 2013. DOI: https://doi.org/10.1109/WPNC.2013.6533293.
RULLAN-LARA, Jose L.; SANAHUJA, Guillaume; LOZANO, Rogelio; SALAZAR, Sergio; GARCIA-HERNANDEZ, Ramon; RUZ-HERNANDEZ, Jose A. Indoor localization of a quadrotor based on WSN: A real-time application. Int. J. Advanced Robotic Syst., v.10, n.1, 2013. DOI: https://doi.org/10.5772/53748.
BLACK, Timothy J.; PATHIRANA, Pubudu N.; NAHAVANDI, Saeid. Position estimation and tracking of an autonomous mobile sensor using received signal strength. Proc. of Int. Conf. on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP, 15-18 Dec. 2008, Sydney, Australia. IEEE, 2008, p.19-24. DOI: https://doi.org/10.1109/ISSNIP.2008.4761956.
MASIERO, A.; FISSORE, F.; GUARNIERI, A.; PIROTTI, F.; VETTORE, A. UAV positioning and collision avoidance based on RSS measurements. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., v.XL-1/W4, p.219-225, 2015. DOI: https://doi.org/10.5194/isprsarchives-XL-1-W4-219-2015.
TIWARI, S.; DARRAJI, R.; BASSAM, S.A.; KWAN, A.; RAWAT, K.; RAWAT, M.; FATTOUCHE, M.; GHANNOUCHI, F.M. Practical result of wireless indoor position estimation by using hybrid TDOA/RSS algorithm. Proc. of 23rd Canadian Conf. on Electrical and Computer Engineering, CCECE, 2-5 May 2010, Calgary, AB, Canada. IEEE, 2010. DOI: https://doi.org/10.1109/CCECE.2010.5575134.
ZHUK, S.Y. Synthesis of digital detector-meters for mixed Markovian processes. Radioelectron. Commun. Syst., v.32, n.11, p.29-35, 1989. URI: http://radioelektronika.org/article/view/S073527271989110063.
TOVKACH, Igor O.; ZHUK, Serhii Ya. Adaptive filtration of parameters of the UAV movement on data from its location calculated on the basis the time difference of arrival method. Proc. of 2017 IEEE First Ukraine Conf. on Electrical and Computer Engineering, UKRCON, 29 May-2 June 2017, Kyiv, Ukraine. IEEE, 2017, p.160-165. DOI: https://doi.org/10.1109/UKRCON.2017.8100466.
TOVKACH, I.O.; ZHUK, S.Y. Recurrent algorithm for TDOA localization in sensor networks. J. Aerosp. Technol. Manag., v.9, n.4, p.489-494, 2017. DOI: http://dx.doi.org/10.5028/jatm.v9i4.727.
TOVKACH, I.O.; ZHUK, S.Y. Adaptive filtration of parameters of the movement UAV according to sensor networks based on measurements of the received signal strength. Visnyk NTUU KPI. Ser. Radiotekhnika. Radioaparatobuduvannya, n.69, p.41-48, 2017.
EVLANOV, P.A.; ZHUK, S.Y. Integration of meters with failures. Radioelectron. Commun. Syst., v.33, n.7, p.49-53, 1990. URI: http://radioelektronika.org/article/view/S073527271990070111.