TY - GEN
T1 - On passive TDOA and FDOA localization using two sensors with no time or frequency synchronization
AU - Yeredor, Arie
PY - 2013/10/18
Y1 - 2013/10/18
N2 - Traditional passive localization based on Time-Difference of Arrival (TDOA) or Frequency-Difference of Arrival (FDOA) usually involves several remote sensors, which require precise time-synchronization and frequency-locking among them. The need for such time or frequency alignment sometimes poses a serious operational challenge on the system. In addition, it is often desired to keep the number of sensors to a minimum. In this work we look into the operationally-simplest scenario in this context: using only two sensors, without any synchronization or locking. When at least one of the sensors, or the transmitting target, is moving at some considerable speed, it is still possible to localize the target, based on a few TDOA and / or FDOA measurements, by considering the time- and frequency-offsets as additional unknown parameters. We analyze the associated performance bound and propose a Maximum Likelihood estimation approach. The attainable accuracy and its dependence on geometry are demonstrated numerically and in simulation.
AB - Traditional passive localization based on Time-Difference of Arrival (TDOA) or Frequency-Difference of Arrival (FDOA) usually involves several remote sensors, which require precise time-synchronization and frequency-locking among them. The need for such time or frequency alignment sometimes poses a serious operational challenge on the system. In addition, it is often desired to keep the number of sensors to a minimum. In this work we look into the operationally-simplest scenario in this context: using only two sensors, without any synchronization or locking. When at least one of the sensors, or the transmitting target, is moving at some considerable speed, it is still possible to localize the target, based on a few TDOA and / or FDOA measurements, by considering the time- and frequency-offsets as additional unknown parameters. We analyze the associated performance bound and propose a Maximum Likelihood estimation approach. The attainable accuracy and its dependence on geometry are demonstrated numerically and in simulation.
KW - FDOA
KW - TDOA
KW - passive localization
KW - two sensors
KW - unlocked
KW - unsynchronized
UR - http://www.scopus.com/inward/record.url?scp=84890514618&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2013.6638423
DO - 10.1109/ICASSP.2013.6638423
M3 - منشور من مؤتمر
SN - 9781479903566
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 4066
EP - 4070
BT - 2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings
T2 - 2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013
Y2 - 26 May 2013 through 31 May 2013
ER -