Abstract
Time difference of arrival (TDOA) positioning is one of the widely applied techniques for locating an emitting source. Unfortunately, synchronization clock bias and random sensor location perturbations are known to significantly degrade the TDOA localization accuracy. This paper studies the use of a set of calibration sources, whose locations are accurately known to an estimator, to reduce the loss in localization accuracy caused by synchronization offsets and sensor location errors. Under the Gaussian noise assumption, we first derive the Cramér–Rao bound (CRB) for parametric estimation with the use of calibration emitters. Some explicit CRB expressions are obtained, and the performance improvement due to the introduction of the calibration sources is also quantified through the CRB analysis. In order to achieve the optimum localization accuracy, we proceed to propose new localization methods using the TDOA measurements from both target source and calibration emitters. Specifically, two dimension-reduction Taylor-series iterative algorithms are developed, and both of them have two stages. The first stage estimates the clock bias and refines the sensor positions by using the calibration TDOA measurements and the prior knowledge of sensor locations. The second stage provides the estimates of source location by combining the TDOA measurements of target signal and the estimated values in the first phase. The mean square errors (MSEs) of the proposed methods are shown analytically to achieve the corresponding CRB by applying the first-order perturbation analysis. Simulations are used to corroborate and support the theoretical development in this paper.
Highlights
Passive localization of an emitting source is a fundamental research topic in numerous applications including signal processing, wireless communications, wireless sensor networks, sonar, surveillance, navigation, passive radar, and vehicular technique
The insight gained from the Cramér–Rao bound (CRB) indicates that the calibration sources can significantly reduce the effects of clock bias and sensor position errors
It can be seen that the proposed algorithms outperform the differential calibration (DC) algorithm and the root-mean-square error (RMSE) improvement increases as σRDOA is increased
Summary
Passive localization of an emitting source is a fundamental research topic in numerous applications including signal processing, wireless communications, wireless sensor networks, sonar, surveillance, navigation, passive radar, and vehicular technique. In order to further improve the source position estimate in the presence of timing synchronization offsets and/or sensor location errors, we need to utilize a set of calibration emitters whose positions are accurately or approximately known. In order to achieve the optimum estimation accuracy, we develop new TDOA localization methods using the measurements from both target source and calibration emitters. (1) The exact CRB expressions for TDOA source localization in the presence of synchronization clock bias and sensor location errors are first obtained. (2) Aiming at the localization problem addressed here, we propose two efficient dimension-reduction Taylor-series iterative algorithms based on the property of the orthogonal projection matrix Both of them can significantly reduce the performance loss in localization accuracy caused by synchronization offsets and sensor location errors. It contains two orthogonal projection matrix formulas for the full-columnrank matrix, the partitioned matrix inversion formula for symmetric matrix, and the matrix inversion lemma
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