Least mean square (LMS) normalizer for active sonar

Communications – electrical: acoustic wave systems and devices – Echo systems – Distance or direction finding

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367901, G01S 1500

Patent

active

053495675

ABSTRACT:
A normalizer based on a Least Mean Square (LMS) adaptive algorithm configured to provide effective normalization when the background noise is locally non-stationary and when the target may be subject to time spread of unknown extent. The LMS algorithm used in the normalizer includes an adaptive filter in both the primary and reference inputs as a means of adapting to variations in both the signal and noise statistics. The LMS algorithm is implemented on the logarithm of the data, so that the difference minimized in the LMS structure drives the ratio of the signal power to noise power to a constant value. The algorithm can be used as a range normalizer by running it over range in each doppler bin, or as a frequency normalizer by operating across doppler in each range bin. By continually adapting to the statistics present in the data, the normalizer more effectively deals with the variations in the noise and signal statistics.

REFERENCES:
patent: 3778822 (1973-12-01), Bauer
patent: 4270223 (1981-05-01), Marston
patent: 5251185 (1993-10-01), Baggenstoss
"An Algorithm for Linear Constrained Adaptive Array Processing," O. L. Frost, III, Proc. IEEE, vol. 60, pp. 926-935, 1972.

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