1. Geolocation of Multiple Noncooperative Emitters Using Received Signal Strength: Sparsity, Resolution, and Detectability
- Author
-
Kurt Bryan and Deborah Walter
- Subjects
Signal Processing (eess.SP) ,General Computer Science ,Computer science ,RSS ,01 natural sciences ,Signal ,sensor networks ,FOS: Electrical engineering, electronic engineering, information engineering ,General Materials Science ,Electrical Engineering and Systems Science - Signal Processing ,compressed sensing ,Attenuation ,010401 analytical chemistry ,General Engineering ,Sparse approximation ,computer.file_format ,signal mapping ,0104 chemical sciences ,Power (physics) ,detection algorithms ,Geolocation ,Compressed sensing ,lcsh:Electrical engineering. Electronics. Nuclear engineering ,Radio frequency ,lcsh:TK1-9971 ,Algorithm ,computer ,Source localization - Abstract
In this paper we investigate the problem of locating multiple non-cooperative radio frequency (RF) emitters using only received signal strength (RSS) data. We assume that the number of emitters is unknown and that individual emitters cannot be distinguished in the RSS data. Moreover, we assume that the environment in which the data has been collected has not been mapped or "fingerprinted" by the prior collection of RSS data. Our primary interest is the limiting resolution that can be obtained by this type of data, and the lowest power emitters that can be detected, as a function of noise level, sensor geometry, and other variables. We formulate the recovery problem as one of sparse approximation or compressed sensing, and investigate an appropriate recovery algorithm for this setting, and use it to illustrate our conclusions. We also include a reconstruction based on sampled data we collected, to illustrate the reasonableness of our parameter choices and conclusions., Comment: 14 pages, 8 figures
- Published
- 2020