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Copyright of Journal of Remote Sensing is the property of Editorial Office of Journal of Remote Sensing & Science Publishing Co. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Remote Sensing is the property of Editorial Office of Journal of Remote Sensing & Science Publishing Co. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Remote Sensing is the property of Editorial Office of Journal of Remote Sensing & Science Publishing Co. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The signal subspace fitting technique is extended to a general polarization sensitive array for direction-of-arrival (DOA) and polarization estimation of coherent signals. Based on the linear relation between the spatial phase matrix and polarization vector, the new method enables uncouple DOA and polarization estimation via an appropriate separation of signal-subspace rotation matrix. Unlike spatial smoothing and polarimetric smoothing, this generalized signal subspace fitting method (GSSF) does not require a certain number of matched subarrays and can be implemented without aperture reduction. It is shown that GSSF is superior to both the spatial smoothing and polarimetric smoothing preprocessed methods in terms of DOA estimation accuracy, especially in the presence of low signal-to-noise ratio values and short data samples. [ABSTRACT FROM AUTHOR]