Volume 32 #4

Contents

1. Threshold duration of sound signals for their sources approaching and withdrawing under condition of high-frequency hearing loss modeling
2. The nature of changes in impulse activity of neurons of hypothalamic supraoptic nucleus following prolonged exposure to vibration
3. Visual acuity of ophthalmologically healthy people and features of form the foveal pit of the retina
4. Characteristics of morphological development of the extreme retinal periphery near ora serrata
5. The effect of local diascleral stimulation of the extreme and middle peripheral parts of the retina on foveal contrast sensitivity and color recognition
6. Neural encoding mechanism of the symmetrical crosses in the visual system
7. Mapping of enclosed buildings using mobile radio tomography
8. Projectively invariant description of non-planar smooth figures. 2. On recognition of ovaloids of revolution

In this paper we consider the task of inner objects mapping for the building with a bunch of moving around it autonomous agents which use narrow beam of radio waves using WiFi frequency (2.4 GHz). Linear model of pixel-wise radio waves attenuation is considered. SIRT algorithm with TV and Tikhonov regularizations is used for the task of tomography reconstruction. Properties of the presented model are studied during simulation using synthetic data consisting of 8 buildings with inner object with different shapes. Mapping quality depends on transmission power is found. Simulation results confirm suggested approach usability.

Key words: Mobile radio tomography, convex optimization, regularization, simulation, robotics

DOI: 10.1134/S0235009218040054

References:

• Sukhanov D. Ya.. Zavialova K. V. Trekhmernaya radiotomografiya obyektov skrytykh za dielektricheski neodnorodnymi pregradami [Three-dimensional radio tomography of objects enclosed by a dielectrically heterogeneous obstacles]. Zhurnal tekhnicheskoy fiziki [The technical physics journal]. 2015. V. 85. № 10. P. 115–120 (in Russian).
• Bardak C., Saed M. Microwave imaging with a time-reversed finite-difference time-domain technique. Journal of Electromagnetic Waves and Applications. 2014. V. 28. № 12. P. 1455–1467. DOI: 10.1080/09205071.2014.929048.
• Batenburg K.J., Helwerda L., Kosters W.A., Van der Meij T. Agents for Mobile Radio Tomography. In: Proceedings of the 28th Benelux Conference on Artificial Intelligence. 2016. P. 17–24.
• Buzmakov A., Ingacheva A., Prun V., Nikolaev D., Chukalina M., Ferrero C. and Asadchikov V. Analysis of Computer Images in the Presence of Metals. Proc. SPIE 10696, Tenth International Conference on Machine Vision (ICMV 2017). 2018. P. 106961B.
• Estrela V.V., Magalhaes H.A., Saotome O. Total Variation Applications in Computer Vision. Handbook of Research on Emerging Perspectives in Intelligent Pattern Recognition, Analysis, and Image Processing. IGI Global. 2016. P. 41–64. DOI: 10.4018/978-1-4666-8654-0.ch002.
• Ganesh, R., Pahlavan K. Effects of traffic and local movements on multipath characteristics of an indoor radio channel. Electronics Letters. 1990. V. 26. № 12. P. 810–812.
• Gockenbach M. Linear Inverse Problems and Tikhonov Regularization. The Mathematical Association of America. 2016. 333 p.
• Helwerda L. Mobile radio tomography: Autonomous vehicle planning for dynamic sensor positions. Master’s thesis. LIACS, Universiteit Leiden. 2016.
• Huang Y., Boyle K. Antennas: from theory to practice. John Wiley & Sons. 2008. DOI: 10.1002/9780470772911.
• Impulse synthetic aperture radar: through-the-wall and underground imaging – Eureka Aerospace. URLhttp:// www.eurekaaerospace.com/content/impulsesyntheticaperture-radar-through-wall-and-under-ground-imaging (accessed: 02.07.2018).
• Ingacheva A., Chukalina M., Khanipov T., Nikolaev D. Blur Kernel Estimation with Algebraic Tomography Technique and Intensity Profiles of Object Boundaries. Proc. SPIE 10696, Tenth International Conference on Machine Vision (ICMV 2017). 2018. P. 1069626B.
• Le Digabel S. Algorithm 909: NOMAD: Nonlinear Optimization with the MADS Algorithm. ACM Transactions on Mathematical Software. 2011. V. 37. № 4. P. 1–15. DOI: 10.1145/1916461.1916468.
• Le Digabel S., Tribes C. The NOMAD software for blackbox optimization. GERAD Newsletter. 2012. V. 9. № 2. P. 6–7.
• Nocedal J., Wright S. J. Numerical Optimization. Springer. 1999. 634 p.
• PulsON 440 – Time Domain. URL: http://www.timedomain.com/products/pulson-440/ (accessed 02.07.2018).
• Shvets E., Nikolaev D. Complex approach to long-term multi-agent mapping in low dynamic environments. Proceedings SPIE. Eighth International Conference on Machine Vision (ICMV 2015). 2015. V. 9875. P. 98752A. DOI: 10.1117/12.2228708.
• Shvets E., Shepelev D., Nikolaev D. Occupancy grid mapping with the use of a forward sonar model by gradient descent. Journal of Communications Technology and Electronics. 2014. V. 61. № 12. P. 1474–1480. DOI: 10.1134/S106422691612024X.
• Tan B., Chetty K., Jamieson K. Thru Mapper: Through-Wall Building Tomography with a Single Mapping Robot. Proceedings of the 18th International Workshop on Mobile Computing Systems and Applications (ACM). 2017. P. 1–6. DOI: 10.1145/3032970.3032973.
• Van der Meij T. Mobile radio tomography: Reconstruction and visualization of wireless sensor networks with dynamically positioned sensors. Master’s thesis, Leiden University. 2016.
• Wilson J., Patwari N. Radio tomographic imaging with wireless networks. IEEE Transactions on Mobile Computing. 2010. V. 9. № 5. P. 621–632. DOI: 10.1109/TMC.2009.174.
• Wilson J., Patwari N. See-through walls: Motion tracking using variance-based radio tomography networks. IEEE Transactions on Mobile Computing. 2011. V. 10. №5. P. 612-621. DOI: 10.1109/TMC.2010.175.