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Local bounds, such as the Cramer–Rao bound (CRB), provide inaccurate predictions under low signal-to-noise ratio (SNR) conditions. Global bounds are capable of providing more accurate predictions of the performance of estimators over the full range of SNR. In this paper, we derive the Ziv–Zakai bound (ZZB) for joint location and velocity estimation of a target illuminated by a non-coherent multiple-input...
Bayesian bounds incorporate prior knowledge on parameters of interest. Nonlocal bounds can provide more accurate prediction of the performance of estimators over the full range of possible mean-squared errors. For example, local bounds, such as the Cramer-Rao bound (CRB), provide especially inaccurate predictions under low signal-to-clutter-plus-noise ratio (SCNR) conditions. In this paper, we derive...
In this paper, moving target tracking performance in multiple input multiple output (MIMO) radar systems with distributed antennas and non-coherent processing is studied. Due to the use of multiple, widely distributed antennas, MIMO radar architectures support both centralized and decentralized tracking techniques. Each receiving radar may contribute to central processing by providing either raw data...
This paper presents the derivation of the Ziv-Zakai bound (ZZB) for the localization problem in a MIMO radar system. The target is positioned in the near-field of a network of radars of arbitrary geometry. The radars have ideal mutual time and phase synchronization. The target location is estimated by coherent processing exploiting the amplitude and phase information between pairs of radars. An analytical...
The Ziv-Zakai bound (ZZB) is developed for the estimation error of a radiating source located in a plane, and observed by sensors widely distributed over the same plane. The source is non-cooperative in the sense that the transmitted waveform and its timing are unknown to the sensors. The sensors do have however, information on the power spectral density of the source. Moreover, sensors have ideal...
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