A computationally efficient blind estimator of polynomial phase signals observed by a sensor array

Alon Amar, Amir Leshem, Alle-Jan van der Veen

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

1 Citation (Scopus)

Abstract

Consider estimating the parameters of polynomial phase signals observed by an antenna array given that the array manifold is unknown (e.g., uncalibrated array). To date, only an approximated maximum likelihood estimator (AMLE) was suggested, however, it involves a multidimensional search over the entire coefficient space. Instead, we propose a two-step estimation approach, termed as SEparate-EStimate (SEES): First, the signals are separated with a blind source separation technique by exploiting the constant modulus property; Then, the coefficients of each polynomial are estimated using a least squares method from the unwrapped phase of the estimated signal. This estimator does not involve any search in the coefficient spaces and its computational complexity increases linearly with respect to the polynomial order, whereas that of the AMLE increases exponentially. Simulations show that the proposed estimator achieves the Cramér-Rao lower bound (CRLB) at moderate or high signal to noise ratio (SNR).
Original languageEnglish
Title of host publication2010 IEEE Sensor Array and Multichannel Signal Processing Workshop
EditorsH Messer, A Nehorai
Place of PublicationLos Alamitos, CA
PublisherIEEE Society
Pages253-256
Number of pages4
ISBN (Print)978-1-4244-9395-1
DOIs
Publication statusPublished - Oct 2010
Event2010 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2010 - Jerusalem, Israel
Duration: 4 Oct 20107 Oct 2010

Workshop

Workshop2010 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2010
Abbreviated titleSAM 2010
CountryIsrael
CityJerusalem
Period4/10/107/10/10

Fingerprint Dive into the research topics of 'A computationally efficient blind estimator of polynomial phase signals observed by a sensor array'. Together they form a unique fingerprint.

Cite this