SOURCE LOCALIZATION WITH SPARSE RECOVERY FOR COHERENT FAR- AND NEAR-FIELD SIGNALS

Date

2015-08-12

Author

Elbir, Ahmet M.
Tuncer, Temel Engin

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In source localization applications, coherency among the signals is an important source of error for parameter estimation. In this paper, a method is proposed to solve the localization problem where there are coherently mixed arbitrary number of far- and near-field sources. In order to estimate the direction-of-arrival (DOA) and the range parameters, compressed sensing (CS) approach is presented where a dictionary matrix is constructed with far- and near-field steering vectors. A sparse vector including the supports of the source signals is estimated in spatial domain. The supports of coherent signals are recovered by using convex minimization techniques. It is shown that the proposed approach recovers the signal components of the array output as well as determining the source locations.

Subject Keywords

DOA estimation, Compressed Sensing, Coherent signals, Far-field, Near-field

URI

https://hdl.handle.net/11511/55805

Conference Name

IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE)

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

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Citation Formats

A. M. Elbir and T. E. Tuncer, “SOURCE LOCALIZATION WITH SPARSE RECOVERY FOR COHERENT FAR- AND NEAR-FIELD SIGNALS,” presented at the IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE), Salt Lake, UT, 2015, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/55805.