A near-field source localization method is proposed for 2-D direction-of-arrival (DOA) and range estimation based on a symmetrical cross array. It first employs the conjugate symmetry property of signal autocorrelation different time delays to construct augmented spatial–temporal cross-correlation matrix, then extended steering vector decoupled avoid usual multidimensional search properties Kha...

In this contribution, Cramer-Rao lower bound (CRLB) for signalto-noise ratio (SNR) estimation from linear modulation signals over flat Rayleigh fading channel is addressed. Therefore, we derive the analytical expressions of Fisher information matrix entries that assess the optimal variance of any unbiased SNR estimator. Based on statistical Monte Carlo computing method, simulation results are d...

A new algorithm for 3D localization in multiplatform radar networks, comprising one transmitter and multiple receivers, is proposed. To take advantage of the monostatic sensor radiation pattern features, ad-hoc constraints are imposed target process. Therefore, problem formulated as a non-convex constrained Least Squares (LS) optimization which globally solved quasi-closed-form leveraging Karus...

The Cramer-Rao bound is obtained for the joint problem of concurrent association and track parameter estimation for the problem of tracking in clutter and tracking multiple targets. Simplified rule-of-thumb expressions are obtained to quantify the possibility and requirements for tracking in heavy clutter. © 1997 Elsevier Science B.V.

The problem of the parameter estimation of chirp signals is addressed. Several closely related estimators are proposed whose main characteristics are simplicity, accuracy, and ease of on-line or off-line implementation. For moderately high signal-to-noise ratios they are unbiased and attain the Cramer-Rao bound. Monte Carlo simulations verify the expected performance of the estimators.

This paper is the second of a two-part paper aimed at studying fundamental limits in estimation in 1D scattering systems via the Cramer-Rao bound. In this paper we provide and discuss computer simulation results illustrating the theory in the first paper.

Absfrucf -A universal nearly efficient estimator is proposed for the first order autoregressive (AR) model where the probability distribution of the driving noise is unknown. The proposed estimator has an intuitively appealing relation to universal data compression and to universal tests for randomness. Index Terms -asymptotically efficient estimation, universal estimation, Cramer-Rao bound, Fi...

A Cramer-Rao bound (CRB) study is developed in onedimensional (1D) space which sheds fundamental insight onto the information about multiply scattering point-like scatterers that is contained in scattering field data corresponding to transmissive, reflective, and combined transmissive plus reflective sensing geometries, and singleand multi-frequency measurements.

In this paper iterative blind estimation of the complex amplitudes of the users is considered. A Gaussian mixture model formulation of the problem is introduced and Expectation Maximization (EM) algorithm for estimation of parameters for Gaussian mixture observation model is used. Simulation results compare the performance of the proposed algorithm with the Cramer-Rao bound.