Design and Analysis of a Non-Iterative Estimator for Target Location in Multistatic Sonar Systems with Sensor Position Uncertainties

Design and Analysis of a Non-Iterative Estimator for Target Location in Multistatic Sonar Systems with Sensor Position Uncertainties

Blog Article

Target location is the basic application of a multistatic sonar system.Determining the position/velocity vector of a target from the related sonar observations is a nonlinear estimation problem.The presence of possible sensor position uncertainties turns this problem into a more challenging hybrid parameter estimation problem.Conventional gradient-based iterative estimators suffer from the problems of initialization difficulties and local convergence.Even if there envox stock is no problem with initialization and convergence, a large computational cost is required in most cases.

In view of these drawbacks, we develop a computationally verragio paradiso efficient non-iterative position/velocity estimator.The main numerical computation involved is the weighted least squares optimization, which makes the estimator computationally efficient.Parameter transformation, model linearization and two-stage processing are exploited to prevent the estimator from iterative computation.Through performance analysis and experimental verification, we find that the proposed estimator reaches the hybrid Cramér−Rao bound and has linear computational complexity.