@inproceedings{a378f5e30a55415da77996a17aa3bc6a,
title = "Recursive Sliding-Window Algorithm for Constrained Multiple-Model MAP Estimation",
abstract = "In this paper, we propose a new algorithm for a recursive implementation of constrained multiple model (MM) maximum a posteriori (MAP) estimation. The recursive procedure is formulated in a sliding window fashion, where the measurements are processed sequentially. For each recursion, an iterative alternating coordinate-ascent (ACA) maximization process and our previously developed constrained sequential list Viterbi algorithm (CSLVA) are used to find the best constrained solution (mode and state sequence estimates) within the window. Performance results from simulation of two application examples are provided to demonstrate the capabilities of the proposed method.",
keywords = "Constrained Estimation, Direct-Search Optimization, MAP, Multiple-Model, Recursive Estimation, Sequential List Viterbi Algorithm, Sliding Window, Trellis",
author = "Ledet, \{Jeffrey H.\} and Jilkov, \{Vesselin P.\} and Li, \{X. Rong\}",
note = "Publisher Copyright: {\textcopyright} 2018 ISIF; 21st International Conference on Information Fusion, FUSION 2018 ; Conference date: 10-07-2018 Through 13-07-2018",
year = "2018",
month = sep,
day = "5",
doi = "10.23919/ICIF.2018.8455611",
language = "英语",
isbn = "9780996452762",
series = "2018 21st International Conference on Information Fusion, FUSION 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1122--1129",
booktitle = "2018 21st International Conference on Information Fusion, FUSION 2018",
}