TY - GEN
T1 - Practical direction of arrival estimator using constrained robust Kalman filtering
AU - Han, Seul Ki
AU - Ra, Won Sang
AU - Park, Jin Bae
PY - 2013
Y1 - 2013
N2 - This paper proposes a linear estimation theory based direction of arrival (DOA) estimator to guarantee high-performance and computational efficiency. To do this, state-space system is derived from the linear prediction relation of the sinusoidal acoustic signal. Since it contains uncertain measurement matrix, the recently developed non-conservative robust Kalman filter (NCRKF) can be applied to compensate the performance degradation by the uncertain measurement matrix. However, unfortunately, the statistical information used in NCRKF scheme may not be precise in actual situation and it leads to the performance degradation. Therefore, in this paper, constrained NCRKF (CNCRKF) is presented to develop practical DOA estimator. It adopts constraint condition derived from the relation between target states to solve the performance degradation problem by the incorrect statistical information. The performance of the proposed solution is demonstrated by the computer simulation.
AB - This paper proposes a linear estimation theory based direction of arrival (DOA) estimator to guarantee high-performance and computational efficiency. To do this, state-space system is derived from the linear prediction relation of the sinusoidal acoustic signal. Since it contains uncertain measurement matrix, the recently developed non-conservative robust Kalman filter (NCRKF) can be applied to compensate the performance degradation by the uncertain measurement matrix. However, unfortunately, the statistical information used in NCRKF scheme may not be precise in actual situation and it leads to the performance degradation. Therefore, in this paper, constrained NCRKF (CNCRKF) is presented to develop practical DOA estimator. It adopts constraint condition derived from the relation between target states to solve the performance degradation problem by the incorrect statistical information. The performance of the proposed solution is demonstrated by the computer simulation.
KW - Direction of arrival (DOA) estimation
KW - robust Kalman filter
KW - source localization and tracking
UR - http://www.scopus.com/inward/record.url?scp=84893608347&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84893608347&partnerID=8YFLogxK
U2 - 10.1109/ICCAS.2013.6704149
DO - 10.1109/ICCAS.2013.6704149
M3 - Conference contribution
AN - SCOPUS:84893608347
SN - 9788993215052
T3 - International Conference on Control, Automation and Systems
SP - 1284
EP - 1287
BT - ICCAS 2013 - 2013 13th International Conference on Control, Automation and Systems
T2 - 2013 13th International Conference on Control, Automation and Systems, ICCAS 2013
Y2 - 20 October 2013 through 23 October 2013
ER -