TY - GEN
T1 - Covariance-free TDoA/FDOA-based moving target localization for multi-static radar
AU - Zhang, Xudong
AU - Wang, Fangzhou
AU - Li, Hongbin
AU - Himed, Braham
N1 - Publisher Copyright:
© 2020 IEEE
PY - 2020/4
Y1 - 2020/4
N2 - In this paper, we consider the problem of estimating the location and velocity of a non-cooperative moving target using a multi-static radar, which consists of a set of spatially distributed sensors in listening mode. The moving target may be transmitting, or reflecting, a source signal that is assumed to be unknown and modeled as a deterministic process. We develop a computationally efficient two-step approach to solve the localization problem. The first step finds the time difference of arrival (TDOA) and frequency difference of arrival (FDOA) estimates for each sensor with respect to a reference sensor by using a 2-dimensional Fast Fourier transform, and the second step employs an iterative reweighted least square (IRLS) approach with a varying weighting matrix to determine the target location and velocity. While most existing TDOA/FDOA-based methods require knowledge of the covariance matrix of the TDOA and FDOA estimates, which is usually unknown in practice, our proposed IRLS approach is covariance matrix-free. Numerical results show that the IRLS approach has a lower signal-to-noise ratio (SNR) threshold compared with a recent TDOA/FDOA-based method, especially when the target is considerably farther away from some sensors than others.
AB - In this paper, we consider the problem of estimating the location and velocity of a non-cooperative moving target using a multi-static radar, which consists of a set of spatially distributed sensors in listening mode. The moving target may be transmitting, or reflecting, a source signal that is assumed to be unknown and modeled as a deterministic process. We develop a computationally efficient two-step approach to solve the localization problem. The first step finds the time difference of arrival (TDOA) and frequency difference of arrival (FDOA) estimates for each sensor with respect to a reference sensor by using a 2-dimensional Fast Fourier transform, and the second step employs an iterative reweighted least square (IRLS) approach with a varying weighting matrix to determine the target location and velocity. While most existing TDOA/FDOA-based methods require knowledge of the covariance matrix of the TDOA and FDOA estimates, which is usually unknown in practice, our proposed IRLS approach is covariance matrix-free. Numerical results show that the IRLS approach has a lower signal-to-noise ratio (SNR) threshold compared with a recent TDOA/FDOA-based method, especially when the target is considerably farther away from some sensors than others.
KW - Iterative approach
KW - Moving target localization
KW - Multi-static passive radar
UR - http://www.scopus.com/inward/record.url?scp=85090323769&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85090323769&partnerID=8YFLogxK
U2 - 10.1109/RADAR42522.2020.9114799
DO - 10.1109/RADAR42522.2020.9114799
M3 - Conference contribution
AN - SCOPUS:85090323769
T3 - 2020 IEEE International Radar Conference, RADAR 2020
SP - 901
EP - 905
BT - 2020 IEEE International Radar Conference, RADAR 2020
T2 - 2020 IEEE International Radar Conference, RADAR 2020
Y2 - 28 April 2020 through 30 April 2020
ER -