Direction of arrival estimation performance comparison of dual cancelled channels space–time adaptive processing techniques. Issue 1 (1st January 2014)

• Record Type: Journal Article
• Authors: Colone, Fabiola; Cristallini, Diego; Cerutti‐Maori, Delphine; Lombardo, Pierfrancesco
• Is Part Of: IET radar, sonar & navigation. Volume 8:Issue 1(2014)
• Page Start: 17
• Page End: 26
• Publication Date: 2014-01-01
• Subjects: direction‐of‐arrival estimation -- echo -- maximum likelihood estimation -- space‐time adaptive processing; direction of arrival estimation -- dual cancelled channels -- space‐time adaptive processing techniques -- digital beamforming -- clutter echoes -- air‐borne space‐time adaptive processing -- AB‐STAP -- generalised monopulse estimator -- dual cancelled channel approach -- ground moving targets -- DOA estimation -- Cramer‐Rao bound -- maximum likelihood estimator; Signal processing -- Periodicals; Radar -- Periodicals; Sonar -- Periodicals; Electronics in navigation -- Periodicals; Navigation -- Periodicals; 621.3848
• DOI: 10.1049/iet-rsn.2012.0368
• Languages: English
• ISSNs: 1751-8784

Abstract

Abstract : This study presents two alternative techniques for the estimation of the target direction of arrival (DOA) for a moving radar equipped with digital beamforming, operating in look‐down against strong clutter echoes. Both the considered techniques, namely AB space–time adaptive processing (AB‐STAP) and generalised monopulse estimator, are based on a dual cancelled channel approach that simplifies their implementation. An extensive performance comparison is presented for the ground moving targets. Both the theoretical and simulated analyses of DOA estimation are performed, which include the comparison to the Cramér‐Rao bound. The considered processing schemes are shown to yield comparable accuracies in target DOA estimation with respect to a maximum likelihood estimator. Moreover, they ensure lower computational cost, since no numerical maximisation of any functional is required. AB‐STAP shows the additional nice property of estimation robustness when a limited set of homogeneous data is available to achieve the adaptivity. The comparison is finally performed applying the different estimators to a set of real multichannel data.