Analytic Sequential Weiss–Weinstein Bounds

In this paper, we explore a sequential Bayesian bound for state-space models focusing on hybrid continuous and discrete random states. We provide an analytic recursion for the sequential Weiss-Weinstein (SWW) bound for linear state-space models with solutions for Gaussian, uniform, and exponential distributions as derived, as well as for a combination of these. We compare the SWW bound for discretized states with the corresponding bound for the continuous states. The SWW bound is contrasted with the sequential Cramér-Rao bound for Gaussian distributions. Practical issues of SWW bounds are discussed and numerical simulation results provide insights into their behavior.