Compressed Localization and Spectrum Sensing for Cognitive Radio and Distributed Radio Surveillance

• Applicants: Professor Dr. Rudolf Mathar; Professor Dr.-Ing. Reiner Thomä
• Subject Area: Electronic Semiconductors, Components and Circuits, Integrated Systems, Sensor Technology, Theoretical Electrical Engineering
• Term: from 2017 to 2019
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 335181839

• Final Report Year: 2019

Final Report Abstract

This project has contributed to the theoretical foundations and advanced experimental research in the area of infrastructure assisted radio surveillance and localization. It has facilitated development of novel approaches to signal detection and localization based on the compressed sensing (CS) paradigm, that find potential application in cognitive radio systems, distributed radio surveillance and by spectrum regulators. One of the main project aims was investigating approaches for distributed CS-based radio surveillance under realistic signal and propagation conditions. To this end, we studied a number of theoretical and practical issues associated with compressed acquisition and processing of radio signals commonly used in spectrum sensing, time difference of arrival (TDOA) and direction of arrival (DOA) estimation as well as TDOA, received signal strength indication (RSSI) and hybrid localization methods. We developed methods for compressive multiband spectrum sensing, compressive narrowband and multiband DOA estimation, and multiband TDOA estimation from compressed measurements. We also applied sparse recovery ideas to TDOA-based and hybrid TDOA/DOA-based localization and investigated synchronization and self-localization aspects of TDOA-based localization in both theoretical and experimental setups. Finally, we have considered the influence of multipath propagation and looked into ways of exploiting propagation modelling, via ray tracing, for localization improvement in complex propagation scenarios. Besides conducting fundamental theoretical studies, we performed a number of experimental tests to verify our findings and evaluate achievable estimation performance. Among others, these included an implementation and testing of an outdoor TDOA localization system based on the software defined radio (SDR) and a development of a testbed for an antenna array compression emulation with antenna measurements from an anechoic chamber.

Publications

• “Design and analysis of compressive antenna arrays for direction of arrival estimation”. In: Signal Processing 138 (2017), pp. 35–47
  M. Ibrahim, V. Ramireddy, A. Lavrenko, J. König, F. Römer, M. Landmann, M. Grossmann, G. Del Galdo, and R. S Thomä
  
• “Distributed software defined radio testbed for real-time emitter localization and tracking”. In: 2017 International Conference on Communications Workshops (ICC Workshops). 2017, pp. 1246–1252
  J. Schmitz, F. Bartsch, M. Hernández, and R. Mathar
  
• “Differential Multidimensional Scaling for Self-Localization of TDOA Sensor Networks”. In: Wireless Communications and Networking Conference (WCNC). 2017, pp. 1–5
  J. Schmitz, S. Shojaee, S. Toledo, R. C. Hincapie, V. Radhakrishnan, and R. Mathar
  
• “Multiband TDoA estimation from sub-Nyquist samples with distributed wideband sensing nodes”. In: IEEE Global Conference on Signal and Information Processing (GlobalSIP 2017). Montreal, Canada, Nov. 2017, pp. 96–100
  A. Lavrenko, F. Römer, Giovanni Del Galdo, and Reiner S. Thomä
  
• “On the Accuracy of Passive Hyperbolic Localization in the Presence of Clock Drift”. In: IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC). Montreal, QC, Canada, Oct. 2017, p. 6
  S. Shojaee, J. Schmitz, R. Mathar, and S. Toledo
  
• “On the SNR variability in noisy compressed sensing”. In: IEEE Signal Processing Letters 24.8 (2017), pp. 1148–1152
  A. Lavrenko, F. Roemer, G. Del Galdo, and R. Thoma
  
• “Sparse framework for hybrid TDOA/DOA multiple emitter localization”. In: IEEE International Symposium on Signal Processing and Information Technology (ISSPIT 2017). Bilbao, Spain, Dec. 2017, pp. 174–179
  R. Hincapie, C. Gomez, A. Lavrenko, L. Betancur, and J. Schmitz
  
• "Sensing Matrix Sensitivity to Random Gaussian Perturbations in Compressed Sensing," 2018 26th European Signal Processing Conference (EUSIPCO), 2018, pp. 583-587
  A. Lavrenko, F. Römer, G. Del Galdo, and R. Thomä
  
• Combining Matrix Design for 2D DoA Estimation with Compressive Antenna Arrays using Stochastic Gradient Descent
  S. Pawar, S. Semper, and F. Römer
  
• “Combining matrix design for 2D DoA estimation with compressive antenna arrays”. In: 22nd International ITG Workshop on Smart Antennas (WSA 2018). Bochum, Germany, Mar. 2018, pp. 1–8
  S. Pawar, A. Lavrenko, M. Ibrahim, F. Römer, G. Del Galdo, and R. S. Thomä
  
• “Compressive Acquisition and Processing of Sparse Analog Signals”. PhD thesis. Technische Universität Ilmenau, July 2018
  A. Lavrenko
  
• “Impact of multipath in a hybrid TDoA/DoA sparse radiolocalization framework”. In: 2018 International Conference on Electromagnetics in Advanced Applications (ICEAA). 2018, pp. 697–700
  R. Hincapie, C. Gomez, L. Betancur, A. Lavrenko, and J. Schmitz
  
• “RSS-based Location and Transmit Power Estimation of Multiple Co-Channel Targets”. In: 15th International Symposium on Wireless Communication Systems (ISWCS’18). Lisbon, Portugal, Aug. 2018, pp. 1–6
  E. Zandi and R. Mathar
  
• “Ultrasound-based Cooperative Indoor Localization for Robotic Applications – Extended Abstract”. In: Microsoft Indoor Localization Competition – IPSN 2018. Porto, Portugal, Apr. 2018, pp. 1–2
  J. Schmitz, O. Peters, and R. Mathar