TY - GEN
T1 - Performance bound for localization of a near field source
AU - Chiriac, Vlad M.
AU - Haimovich, Alexander M.
AU - Schwartz, Stuart C.
AU - Dabin, Jason A.
PY - 2009
Y1 - 2009
N2 - The Ziv-Zakai bound (ZZB) is developed for the estimation error of a radiating source located in a plane, and observed by sensors widely distributed over the same plane. The source is non-cooperative in the sense that the transmitted waveform and its timing are unknown to the sensors. The sensors do have however, information on the power spectral density of the source. Moreover, sensors have ideal mutual time and phase synchronization. The source location is estimated by coherent processing exploiting the amplitude and phase information between pairs of sensors. An analytical expression is developed for the ZZB relating the estimation error to the carrier frequency, signal bandwidth, the number of sensors, and their location. Numerical examples demonstrate that the ZZB closely predicts the performance of the maximum likelihood estimate across the full range of signal to noise ratio (SNR) values. At low SNR, the ZZB bound demonstrates performance dominated by noise, at medium SNR, the performance is dictated by the presence of sidelobes in the localization metric, and at high SNR, it is shown that the ZZB converges to the Cramer-Rao bound.
AB - The Ziv-Zakai bound (ZZB) is developed for the estimation error of a radiating source located in a plane, and observed by sensors widely distributed over the same plane. The source is non-cooperative in the sense that the transmitted waveform and its timing are unknown to the sensors. The sensors do have however, information on the power spectral density of the source. Moreover, sensors have ideal mutual time and phase synchronization. The source location is estimated by coherent processing exploiting the amplitude and phase information between pairs of sensors. An analytical expression is developed for the ZZB relating the estimation error to the carrier frequency, signal bandwidth, the number of sensors, and their location. Numerical examples demonstrate that the ZZB closely predicts the performance of the maximum likelihood estimate across the full range of signal to noise ratio (SNR) values. At low SNR, the ZZB bound demonstrates performance dominated by noise, at medium SNR, the performance is dictated by the presence of sidelobes in the localization metric, and at high SNR, it is shown that the ZZB converges to the Cramer-Rao bound.
KW - Parameter estimation
KW - Performance bounds
KW - Source localization
UR - http://www.scopus.com/inward/record.url?scp=77953864762&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77953864762&partnerID=8YFLogxK
U2 - 10.1109/ACSSC.2009.5470148
DO - 10.1109/ACSSC.2009.5470148
M3 - Conference contribution
AN - SCOPUS:77953864762
SN - 9781424458271
T3 - Conference Record - Asilomar Conference on Signals, Systems and Computers
SP - 130
EP - 135
BT - Conference Record - 43rd Asilomar Conference on Signals, Systems and Computers
T2 - 43rd Asilomar Conference on Signals, Systems and Computers
Y2 - 1 November 2009 through 4 November 2009
ER -