Sparse framework for hybrid TDoA/DoA multiple emitter localization
- Resource Type
- Conference
- Authors
- Hincapie, Roberto; Gomez, Cristina; Betancur, Leonardo; Lavrenko, Anastasia; Schmitz, Johannes
- Source
- 2017 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT) Signal Processing and Information Technology (ISSPIT), 2017 IEEE International Symposium on. :174-179 Dec, 2017
- Subject
- Communication, Networking and Broadcast Technologies
Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Estimation
Dictionaries
Direction-of-arrival estimation
Time measurement
Sensors
Antenna arrays
Task analysis
- Language
In this paper, we consider the problem of localizing multiple non-collaborative transmitters by a network of distributed sensor nodes. The nodes are equipped with versatile sensing capabilities allowing them to estimate the time differences of arrival (TDoAs) and/or the directions of arrival (DoAs) of the incoming waves. We formulate the localization task as a joint block-sparse recovery problem and develop a framework that allows to accommodate different types of measures, such as the beamformer outputs in case of DoAs or cross-correlation functions in case of TDoAs. We then propose a reduced-size location recovery approach in which we perform multiple location estimations from partial combinations of measures that are later fused together. Our results indicate that in doing so we can achieve estimation performance superior to that of the fully joint recovery, while keeping a lower computational complexity.