An Efficient Weighted Least Squares Estimator for Elliptic Localization in Distributed MIMO Radars

Target Localization Using Double-Sided Bistatic Range Measurements in Distributed MIMO Radar Systems

“…In practice, we apply the approximated W using estimated bolddt and bolddr via a least square (LS) approach (substituting an identity matrix for W in (20)) as in previous methods [6,7,8,9,10,11,12,13,14,15]. Note that, instead of error covariance matrix, Cov[ε], we use the diagonal terms of Cov[ε] for W , since Cov[ε] is not invertible here.…”

“…As target-mediated time delays are nonlinear, estimation of target location via direct analysis of these delays is difficult. Hence, several approaches seeking to linearize the relationship between the target and the time delays have been proposed [4,5,6,7,8,9,10,11,12,13,14,15]. Of these, algorithms based on bistatic range measurements (BRMs), which are the sum of target–transmitter and target–receiver distances, are introduced in [6,7,8,9,10,11,12,13,14,15].…”

“…A single stage algorithm based on BRM, introduced first in [6,7], estimates the target position with the help of auxiliary parameters (distances between the target and transmitters or distances between the target and receivers). Multistage algorithms, such as those in [8,9,10,11,12,13,14,15], further refine the target position by re-using the estimates of the first-stage BRM method and exploiting their relationships, and asymptotically attain the Cramer–Rao lower bound (CRLB) [12] assuming accurate estimates of the first stage. A recent study [15] shows that the choice of auxiliary parameters (target–transmitter side or target–receiver side) in BRM methods affects the target estimation accuracy.…”

“…Furthermore, the proposed approach can be applied to the second-stage of the multistage BRM algorithms, such as in those of [8,9,10,11,12,13,14,15]. The existing multistage algorithms can be divided into two types depending on the way of linearizing the nonlinear relations between target position and auxiliary parameters estimated in the first stage: the algorithms in [8,9,10,11,12] linearize nonlinear relationships by squaring them and the algorithms in [13,14,15] use first-order Taylor expansion to this end. We present two types of double-sided two-stage BRM algorithms by applying our approach to the most recent multistage BRM algorithms, i.e., two-stage methods using squared Taylor approximated relationships.…”

Efficient closed‐form estimator for joint elliptic and hyperbolic localisation in multistatic system

“…Introduction: It is often of interest to determine the location of a single target in multistatic localisation system, which has drawn considerable attention in recent years. The typical multistatic localisation systems include the multistatic passive radar [1], multistatic sonar [2], multiple-input multiple-output radar [3], and wireless sensor networks. Multistatic system consists of multiple transmitter-receiver pairs, offering more flexibility and better system robustness as well as improved localisation accuracy.…”