&lt;title&gt;Single-scan tracking using N infrared sensors&lt;/title&gt;

Rudd, Jack G.; Marsh, Richard A.

doi:10.1117/12.139387

Cited by 2 publications

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“…The ultimate concept in central-level fusion, for which only one observation per satellite is required, is discussed in [14]. Our claim for it today is hmited to the statement that tactical parameters can be estimated surprisingly well using only one observation per satellite.…”

Section: Sensor Fusionmentioning

confidence: 97%

Surveillance and tracking of ballistic missile launches

Rudd¹,

Marsh²,

Roecker³

1994

IBM J. Res. & Dev.

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This paper begins with an overview of system requirements and design issues that must be considered in the design of algorithms and software for the surveillance and tracking of ballistic missile launches. Detection and tracking algorithms and approaches are then described for the processing of data from a single satellite and from multiple satellites. We cover track formation, missile detection, track extension, and global arbitration, and indicate how these functions fit together coherently.

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Section: Sensor Fusionmentioning

confidence: 97%

Surveillance and tracking of ballistic missile launches

Rudd¹,

Marsh²,

Roecker³

1994

IBM J. Res. & Dev.

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“…These models were divided, based on the extent to which priori information of missile was acquired, into three categories: (a) the template-based model, [2][3][4][5][6][7] (b) the dynamical model, [8][9][10][11] and (c) the polynomial model. [12][13][14][15][16] The estimation accuracy of the templatebased model and the dynamical model depends on the matching of the actual motion of the target with the model.…”

Section: Introductionmentioning

confidence: 99%

Adaptive estimation algorithm of boost-phase trajectory using binary asynchronous observation

Chen

Lei

et al. 2016

Proceedings of the Institution of Mechanical Engineers, Part G:

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A kind of adaptive filter algorithm based on the estimation of the unknown input is proposed for studying the adaptive adjustment of process noise variance of boost phase trajectory. Polynomial model is used as the motion model of the boost trajectory, truncation error is regarded as an equivalent to the process noise and the unknown input and process noise variance matrix is constructed from the estimation value of unknown input according to the quantitative relationship among the unknown input, the state estimation error, and optimal process noise variance. The simulation results show that in the absence of prior information, the unknown input is estimated effectively in terms of magnitude, a positive definite matrix of process noise covariance which is close to the optimal value is constructed real-timely, and the state estimation error approximates the error lower bound of the optimal estimation. The estimation accuracy of the proposed algorithm is similar to that of the current statistical model algorithm using accurate prior information.

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<title>Single-scan tracking using N infrared sensors</title>

Cited by 2 publications

References 0 publications

Surveillance and tracking of ballistic missile launches

Surveillance and tracking of ballistic missile launches

Adaptive estimation algorithm of boost-phase trajectory using binary asynchronous observation

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