A Fresh Look at the Bayesian Bounds of the Weiss-Weinstein Family
IEEE Transactions on Signal Processing
Explicit Ziv-Zakai lower bound for bearing estimation
IEEE Transactions on Signal Processing
Range Compression and Waveform Optimization for MIMO Radar: A CramÉr–Rao Bound Based Study
IEEE Transactions on Signal Processing
Performance Bounds and Angular Resolution Limit for the Moving Colocated MIMO Radar
IEEE Transactions on Signal Processing
Weiss–Weinstein Lower Bounds for Markovian Systems. Part 1: Theory
IEEE Transactions on Signal Processing
Weiss–Weinstein Lower Bounds for Markovian Systems. Part 2: Applications to Fault-Tolerant Filtering
IEEE Transactions on Signal Processing
Extended Ziv-Zakai lower bound for vector parameter estimation
IEEE Transactions on Information Theory
A general class of lower bounds in parameter estimation
IEEE Transactions on Information Theory
Some lower bounds on signal parameter estimation
IEEE Transactions on Information Theory
A lower bound on the estimation error for certain diffusion processes
IEEE Transactions on Information Theory
A lower bound on the mean-square error in random parameter estimation (Corresp.)
IEEE Transactions on Information Theory
A bound on mean-square estimation error with background parameter mismatch
IEEE Transactions on Information Theory
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Several works have suggested that a multi-input multi-output (MIMO) radar system offers improvement in terms of performance in comparison with classical phased-array radar. However, under the widely spread assumption of a uniform a priori distribution for one parameter of interest, there is no result concerning lower bounds on the mean-square error in the case of a Gaussian observation model with parameterized mean. This Fast Communication fills this lack by using the Weiss-Weinstein bound (WWB) which can be calculated under this difficult scenario. As we will show, the proposed bound for MIMO Radar with colocated linear arrays has no closed-form expression. To solve this problem, we propose a closed-form approximation that, as we will show by simulations, is close to the actual bound. This approximated bound is then analyzed for a design purpose in terms of array geometry. Simulations confirm the good ability of the proposed bound to predict the mean square error (MSE) of the maximum a posteriori (MAP) in all ranges of SNR. Particularly, the tightness of the bound to predict the SNR threshold effect is shown.