This Matlab model and the included results are submitted as reference for the paper ''. 

Presenting a comparative study of the Sequential Unscented Kalman Filter (SUKF), Least-squares (LS) Multilateration and standard Unscented Kalman Filter (UKF) for localisation that relies on sequentially received datasets. 

The KEWLS and KKF approach presents a novel solution using Linear Kalman Filters (LKF) to extrapolate individual sensor measurements to a synchronous point in time for use in LS Multilateration. 

 

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[1] Ben Meunier, "KEWLS and KFF 2D Comparative Model", IEEE Dataport, 2021. [Online]. Available: http://dx.doi.org/10.21227/ad95-kj50. Accessed: Jul. 22, 2024.
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doi = {10.21227/ad95-kj50},
url = {http://dx.doi.org/10.21227/ad95-kj50},
author = {Ben Meunier },
publisher = {IEEE Dataport},
title = {KEWLS and KFF 2D Comparative Model},
year = {2021} }
TY - DATA
T1 - KEWLS and KFF 2D Comparative Model
AU - Ben Meunier
PY - 2021
PB - IEEE Dataport
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Ben Meunier. (2021). KEWLS and KFF 2D Comparative Model. IEEE Dataport. http://dx.doi.org/10.21227/ad95-kj50
Ben Meunier, 2021. KEWLS and KFF 2D Comparative Model. Available at: http://dx.doi.org/10.21227/ad95-kj50.
Ben Meunier. (2021). "KEWLS and KFF 2D Comparative Model." Web.
1. Ben Meunier. KEWLS and KFF 2D Comparative Model [Internet]. IEEE Dataport; 2021. Available from : http://dx.doi.org/10.21227/ad95-kj50
Ben Meunier. "KEWLS and KFF 2D Comparative Model." doi: 10.21227/ad95-kj50