Multisensory Prediction Fusion of Nonlinear Functions of the State Vector in Discrete-Time Systems

Song, Ha Ryong; Song, Il Young; Shin, Vladimir

doi:10.1155/2015/249857

Cited by 2 publications

(2 citation statements)

References 28 publications

(69 reference statements)

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“…Real-time SLV tracking problem has made use of single model filters such as an alpha-beta-gamma filter or Kalman filter (KF), 3 because of a reliability issue. However, since a KF only utilizes a single dynamic model, in general, the tracking performance of KF for a maneuvering launch vehicle is inferior to multiple model estimators.…”

Section: Introductionmentioning

confidence: 99%

Distributed multiple model extended information filter with unbiased mixing for satellite launch vehicle tracking

Song

Choi

2018

International Journal of Distributed Sensor Networks

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A distributed extended information filter-based interacting multiple model estimator with unbiased mixing is proposed for satellite launch vehicle tracking. In this problem, multiple heterogeneous sensors such as radars, telemetry systems receiving onboard Global Positioning System—inertial navigation system data, and electro-optical targeting systems are used. The extended information filter is used for nonlinear estimation dealing with ballistic model and spherical coordinate observation. The multiple Markov switching models comprise thrusting and coasting modes having different state vector dimensions for the launch vehicle. To effectively combine both state vectors, an unbiased mixing technique is applied and then the distributed extended information filter integrates local states and information matrix contributions. Hence, the proposed algorithm takes into account both heterogeneity of tracking sensors and multiplicity of vehicle’s dynamic model. We prove the superiority of the proposed algorithm by conducting Monte Carlo simulation with nominal trajectory data of Korea Space Launch Vehicle-1. Comparative simulation results demonstrate that the performance of the proposed method has been improved in vehicle’s position root mean square error.

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Section: Introductionmentioning

confidence: 99%

Distributed multiple model extended information filter with unbiased mixing for satellite launch vehicle tracking

Song

Choi

2018

International Journal of Distributed Sensor Networks

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“…Prediction or fixed-lead prediction in mean square means the synchronization of the slaving data is the estimation of the state at a future time + , where > 0 beyond the observation interval; that is, based on data up to an earlier time [20,24],…”

mentioning

confidence: 99%

Multiple Model-Based Synchronization Approaches for Time Delayed Slaving Data in a Space Launch Vehicle Tracking System

Song

Choi

2016

Mathematical Problems in Engineering

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Due to the inherent characteristics of the flight mission of a space launch vehicle (SLV), which is required to fly over very large distances and have very high fault tolerances, in general, SLV tracking systems (TSs) comprise multiple heterogeneous sensors such as radars, GPS, INS, and electrooptical targeting systems installed over widespread areas. To track an SLV without interruption and to hand over the measurement coverage between TSs properly, the mission control system (MCS) transfers slaving data to each TS through mission networks. When serious network delays occur, however, the slaving data from the MCS can lead to the failure of the TS. To address this problem, in this paper, we propose multiple model-based synchronization (MMS) approaches, which take advantage of the multiple motion models of an SLV. Cubic spline extrapolation, prediction through anα-β-γfilter, and a single model Kalman filter are presented as benchmark approaches. We demonstrate the synchronization accuracy and effectiveness of the proposed MMS approaches using the Monte Carlo simulation with the nominal trajectory data of Korea Space Launch Vehicle-I.

show abstract

Multisensory Prediction Fusion of Nonlinear Functions of the State Vector in Discrete-Time Systems

Cited by 2 publications

References 28 publications

Distributed multiple model extended information filter with unbiased mixing for satellite launch vehicle tracking

Distributed multiple model extended information filter with unbiased mixing for satellite launch vehicle tracking

Multiple Model-Based Synchronization Approaches for Time Delayed Slaving Data in a Space Launch Vehicle Tracking System

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