This is the fifth part of a series of papers that provide a comprehensive survey of techniques
for tracking maneuvering targets without addressing the so-called measurement-origin …

An approach to detection and diagnosis of multiple failures in a dynamic system is
proposed. It is based on the interacting multiple-model (IMM) estimation algorithm, which is …

Target tracking is a hybrid estimation problem involving both continuous and discrete
uncertainties [31]. In the prevailing approaches to target tracking, the modeling of the target …

This is the fourth part of a series of papers that provide a comprehensive survey of
techniques for tracking maneuvering targets without addressing the so-called measurement …

A general multiple-model (MM) estimator with a variable structure (VSMM), railed model-
group switching (MGS) algorithm, is presented. It assumes that the total set of models can be …

For pt. I see ibid., vol. 41, p. 487-93 (1996). An important, natural, and practical approach to
variable-structure multiple-model (VSMM) estimation is the recursive adaptive model-set …

For pt. IV see ibid., vol. 35, no. 1, p. 242-254 (1999). A multiple-model (MM) estimator with a
variable structure, called likely-model set (LMS) algorithm, is presented, which is generally …

Markovian jump systems (MJSs) evolve in a jump-wise manner by switching among simpler
models, according to a finite Markov chain, whose parameters are commonly assumed …

In this paper, an optimization-based adaptive Kalman filtering method is proposed. The
method produces an estimate of the process noise covariance matrix Q by solving an …

A new class of variable-structure (VS) algorithms for multiple-model (MM) estimation is
presented, referred to as expected-mode augmentation (EMA). In the EMA approach, the …