TY - GEN
T1 - Multitone sensor gain calibration in an uncertain underwater environment
AU - Avital, I.
AU - Tabrikian, J.
AU - Messer, H.
N1 - Publisher Copyright:
© 2000 IEEE.
PY - 2000/1/1
Y1 - 2000/1/1
N2 - Array processing techniques for source detection and localization in an underwater acoustic environment are highly sensitive to both environmental modeling errors, such as sound propagation conditions, and sensor gain mismatch. Sonar arrays, which are normally rigorously calibrated before placement, may develop gain mismatch due to mechanical failures or local environmental variations, such as sediment build-up. In order to avoid performance degradation of detection and localization algorithms, a sensor gain calibration process can be carried out periodically. This paper proposes a maximum likelihood algorithm for sensor gain calibration in a shallow water environment. In the presence of environmental uncertainties, a robust algorithm is required, and such an algorithm is consequentially developed. The proposed method is based on the simultaneous estimation of the relative gains and the acoustic transfer function. To improve the accuracy of the sensor gain estimation, a-priori knowledge of the relationship between the sensor gains at different frequencies is exploited. The performance of the proposed calibration method is evaluated via simulations.
AB - Array processing techniques for source detection and localization in an underwater acoustic environment are highly sensitive to both environmental modeling errors, such as sound propagation conditions, and sensor gain mismatch. Sonar arrays, which are normally rigorously calibrated before placement, may develop gain mismatch due to mechanical failures or local environmental variations, such as sediment build-up. In order to avoid performance degradation of detection and localization algorithms, a sensor gain calibration process can be carried out periodically. This paper proposes a maximum likelihood algorithm for sensor gain calibration in a shallow water environment. In the presence of environmental uncertainties, a robust algorithm is required, and such an algorithm is consequentially developed. The proposed method is based on the simultaneous estimation of the relative gains and the acoustic transfer function. To improve the accuracy of the sensor gain estimation, a-priori knowledge of the relationship between the sensor gains at different frequencies is exploited. The performance of the proposed calibration method is evaluated via simulations.
KW - Acoustic propagation
KW - Acoustic sensors
KW - Acoustic signal detection
KW - Array signal processing
KW - Calibration
KW - Frequency estimation
KW - Mechanical sensors
KW - Sensor arrays
KW - Underwater acoustics
KW - Underwater tracking
UR - http://www.scopus.com/inward/record.url?scp=84949563634&partnerID=8YFLogxK
U2 - 10.1109/SAM.2000.877978
DO - 10.1109/SAM.2000.877978
M3 - Conference contribution
AN - SCOPUS:84949563634
T3 - Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop
SP - 107
EP - 111
BT - Proceedings of the 2000 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAME 2000
PB - Institute of Electrical and Electronics Engineers
T2 - IEEE Sensor Array and Multichannel Signal Processing Workshop, SAME 2000
Y2 - 16 March 2000 through 17 March 2000
ER -