Cross-product algorithms for source tracking using an EM vector sensor

Arye Nehorai; Petr Tichavsky

doi:10.1109/icassp.1999.761323

Cross-product algorithms for source tracking using an EM vector sensor

Arye Nehorai, Petr Tichavsky

Research output: Contribution to journal › Conference article › peer-review

2 Scopus citations

Abstract

We present two adaptive cross-product algorithms for tracking the direction to a moving source using an electromagnetic vector sensor. The first is a cross-product algorithm with a forgetting factor, for which we analyze the performance and derive an asymptotic expression of the variance of angular estimation error. We find the optimal forgetting factor that minimizes this variance. The second is a Kalman filter combined with the cross-product algorithm, which is applicable when the angular acceleration of the source is approximately constant.

Original language	English
Pages (from-to)	2781-2784
Number of pages	4
Journal	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume	5
DOIs	https://doi.org/10.1109/icassp.1999.761323
State	Published - 1999
Event	Proceedings of the 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP-99) - Phoenix, AZ, USA Duration: Mar 15 1999 → Mar 19 1999

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abstract = "We present two adaptive cross-product algorithms for tracking the direction to a moving source using an electromagnetic vector sensor. The first is a cross-product algorithm with a forgetting factor, for which we analyze the performance and derive an asymptotic expression of the variance of angular estimation error. We find the optimal forgetting factor that minimizes this variance. The second is a Kalman filter combined with the cross-product algorithm, which is applicable when the angular acceleration of the source is approximately constant.",

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doi = "10.1109/icassp.1999.761323",

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AU - Nehorai, Arye

AU - Tichavsky, Petr

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AB - We present two adaptive cross-product algorithms for tracking the direction to a moving source using an electromagnetic vector sensor. The first is a cross-product algorithm with a forgetting factor, for which we analyze the performance and derive an asymptotic expression of the variance of angular estimation error. We find the optimal forgetting factor that minimizes this variance. The second is a Kalman filter combined with the cross-product algorithm, which is applicable when the angular acceleration of the source is approximately constant.

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U2 - 10.1109/icassp.1999.761323

DO - 10.1109/icassp.1999.761323

M3 - Conference article

AN - SCOPUS:0032626606

SN - 0736-7791

VL - 5

SP - 2781

EP - 2784

JO - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

JF - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

T2 - Proceedings of the 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP-99)

Y2 - 15 March 1999 through 19 March 1999

ER -

Cross-product algorithms for source tracking using an EM vector sensor

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