Conditional and Unconditional Cramér–Rao Bounds for Near-Field Source Localization

Abstract

Near-field source localization problem by a passive antenna array makes the assumption that the time-varying sources are located near the antenna. In this context, the far-field assumption (i.e. planar wavefront) is, of course, no longer valid and one has to consider a more complicated model parameterized by the bearing (as in the far-field case) and by the distance, named range, between the source and a reference coordinate system. One can find a plethora of estimation schemes in the literature, but their ultimate performance in terms of Mean Square Error (MSE) have not been fully investigated. To characterize these performance, the Cramér-Rao Bound (CRB) is a popular mathematical tool in signal processing. The main cause for this is that the MSE of several high-resolution direction of arrival algorithms are known to achieve the CRB under quite general/weak conditions. In this correspondence, we derive and analyze the so-called conditional and unconditional CRBs for a single time-varying near-field source. In each case, we obtain non matrix closed-form expressions. Our approach has two advantages: (i) due to the fact that one has to inverse the Fisher information matrix, the computational cost for a large number of snapshots (in the case of the conditional CRB) and/or for a large number of sensors (in the case of the unconditional CRB), of a matrix-based CRB can be high while our approach is low and (ii) some useful information can be deduced from the behavior of the bound. In particular, an explicit relationship between the conditional and the unconditional CRBs is provided and one shows that closer is the source from the array and/or higher is the signal carrier frequency, better is the range estimation.

Computationally efficient near-field source localization using third-order moments

“…The sensor noise is assumed to be spatial white complex Gaussian, and the signal-to-noise ratio(SNR) is defined relative to each signal. For comparison, we simultaneously execute the high-order ESPRIT method [11,12] and the near-field Cramer-Rao bound (CRB) [18]. Note that the high-order ESPRIT method is based on a ULA with evennumbered sensors, so we adopt 16 from the average results of 500 independent Monte Carlo simulations.…”

Nonuniform linear antenna arrays for enhanced near field source localization

“…1. The array centroid is assumed to be at the origin O, which allows for a more compact expressions of the CRB, compared to [2,6]. A source S emits a narrowband signal s(t) (with wavelength λ) in the direction of the antenna array.…”

Three-Dimensional Localization Algorithm for Mixed Near-Field and Far-Field Sources Based on Esprit and Music Method

“…Note that 1-DML algorithm uses the same ULA aligned with the Z axes with the proposed algorithm. In addition, the related CRLBs [21,22,32,33] are given in the following relevant figures. Note that as [34], the estimation performance of the range parameter is only for NF source in the following each experiment, and we would not give the estimation performance of the range parameter of FF source although the range parameter of FF source can be obtained by (28).…”