TY - JOUR
T1 - Effects of Model Errors on Waveform Estimation Using the MUSIC Algorithm
AU - Friedlander, Benjamin
AU - Weiss, Anthony J.
N1 - Funding Information:
Manuscript received June 27, 1992; revised January 15, 1993. The associate editor coordinating the review of this paper was Prof. Daniel Fuhrmann. This work was supported by the United States Army Research Office under contract DAAL03-91-C-0022, sponsored by the U.S. Army Communications Electronics Command, Center for Signal Warfare. B. Friedlander is with the Department of Electrical and Computer Engineering, University of California, Davis, CA 95616. A. J. Weiss is with the Department of Electrical Engineering, Tel-Aviv University, Tel-Aviv, 69978, Israel. IEEE Log Number 9213293.
PY - 1994/1
Y1 - 1994/1
N2 - Sensor arrays are frequently used to separate and reconstruct superimposed signals arriving from different directions. The paper studies the effect of model errors, i.e., differences between the assumed and actual array response, on the quality of the reconstructed signals. Model errors are the limiting factor of array performance when the observation time is sufficiently long. In this paper, we analyze a signal estimation technique which is based on the MUSIC algorithm. Formulas are derived for the signal-to-interference and signal-to-noise ratios as function of the model errors. By evaluating these formulas for selected test cases we gain some insights into the sensitivity of the signal estimation problem to model uncertainty.
AB - Sensor arrays are frequently used to separate and reconstruct superimposed signals arriving from different directions. The paper studies the effect of model errors, i.e., differences between the assumed and actual array response, on the quality of the reconstructed signals. Model errors are the limiting factor of array performance when the observation time is sufficiently long. In this paper, we analyze a signal estimation technique which is based on the MUSIC algorithm. Formulas are derived for the signal-to-interference and signal-to-noise ratios as function of the model errors. By evaluating these formulas for selected test cases we gain some insights into the sensitivity of the signal estimation problem to model uncertainty.
UR - http://www.scopus.com/inward/record.url?scp=0028257231&partnerID=8YFLogxK
U2 - 10.1109/78.258129
DO - 10.1109/78.258129
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AN - SCOPUS:0028257231
VL - 42
SP - 147
EP - 155
JO - IEEE Transactions on Signal Processing
JF - IEEE Transactions on Signal Processing
SN - 1053-587X
IS - 1
ER -