TY - GEN
T1 - Enhanced DOA visibility of correlated sources for multistatic shipborne surface wave radar
AU - Li, Bo
AU - Xu, Bin
AU - Yuan, Yeshu
PY - 2009
Y1 - 2009
N2 - A modified array interpolation approach to correlated source localization is presented for the surface wave radar (SWR) that employs multiple uniform linear subarrays (ULSAs) mounted on different ships to compose a multistatic shipborne SWR receiving array. This approach that overcomes the main shortcomings of some existing interpolation techniques, comprises three stages: a first stage for preestimating direction-of-arrivals (DOAs) on an assumption that at least a single ULSA is available for correlated source localization, a second stage for specifying a union of nonoverlapping narrow subsectors as the interpolated sector to cover only the preestimates, and a third stage for reestimating DOAs with the virtual uniform linear array (VULA), in which we skip noise prewhitening and appropriately increase the amount of forward/backward spatial smoothing (FBSS) that plays a major role in lowering noise floor while decorrelating correlated sources. Monte Carlo simulations demonstrate the validity of our proposal.
AB - A modified array interpolation approach to correlated source localization is presented for the surface wave radar (SWR) that employs multiple uniform linear subarrays (ULSAs) mounted on different ships to compose a multistatic shipborne SWR receiving array. This approach that overcomes the main shortcomings of some existing interpolation techniques, comprises three stages: a first stage for preestimating direction-of-arrivals (DOAs) on an assumption that at least a single ULSA is available for correlated source localization, a second stage for specifying a union of nonoverlapping narrow subsectors as the interpolated sector to cover only the preestimates, and a third stage for reestimating DOAs with the virtual uniform linear array (VULA), in which we skip noise prewhitening and appropriately increase the amount of forward/backward spatial smoothing (FBSS) that plays a major role in lowering noise floor while decorrelating correlated sources. Monte Carlo simulations demonstrate the validity of our proposal.
UR - https://www.scopus.com/pages/publications/69949098185
U2 - 10.1109/RADAR.2009.4977102
DO - 10.1109/RADAR.2009.4977102
M3 - 会议稿件
AN - SCOPUS:69949098185
SN - 9781424428717
T3 - IEEE National Radar Conference - Proceedings
BT - 2009 IEEE Radar Conference, RADAR 2009
T2 - 2009 IEEE Radar Conference, RADAR 2009
Y2 - 4 May 2009 through 8 May 2009
ER -