doi: 10.52899/24141437_2025_04_545
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Dynamic Filter Improvement

Самаров Е. К.
Article language:
Citation Link: Samarov EK. Dynamic Filter Improvement. Transactions of the Saint Petersburg State Marine Technical University. 2025;4(4):545–552. DOI: 10.52899/24141437_2025_04_545 EDN: LDULAD

Annotation

BACKGROUND: One of the areas for further improvement of spectral filter analysis of random signals is the transition from conventional narrow-band filters to non-stationary narrow-band dynamic filters operating in a transient mode, allowing to increase the measurement accuracy of the estimated spectral power density with conventional and dynamic filters of the same order. AIM: This work aimed to improve procedural algorithms, generalized expressions for the spectral window function, the relative dispersion of the measured spectral power density estimate, and optimal synthesis of the tuning laws for the narrow-band dynamic filters, including the attenuation ratio, carrier frequency, and transmission ratio in the analysis bandwidth, for spectral analysis of random signals. METHODS: To determine the relative dispersion of the estimated spectral power density, a correlation filter method using narrow-band dynamic second-order filters is used. RESULTS: The paper develops and specifies theoretical results in relation to narrow-band second-order dynamic filters to optimize their tuning (measurement) laws with the focus on a more advanced correlation filter method of spectral analysis of random signals. CONCLUSION: The findings show that narrow-band dynamic filters reordered in the analysis bandwidth allow for higher accuracy of spectral analysis compared to conventional steady-state filters of the same order. Keywords: spectral analysis; spectral power density; dynamic filter.

Bibliography

1. Huelsman L, Allen P. Introduction to the Theory and Design of Active Filters. Moscow: Radio i Svyaz; 1984. (In Russ.)
2. Moschytz G, Horn P. Active Filter Design. Moscow: Mir; 1984. (In Russ.)
3. Chinkov VN. Optimization of the tuning laws for second-order dynamic filter characteristics for spectral analysis of random signals. Izmeritel’naya Tekhnika. 2003;(11):61-65. (In Russ.) EDN: PDAIBH
4. Gonorovsky IS. Radio Circuits and Signals. Moscow: Radio i Svyaz; 1986. (In Russ.)
5. Artyushenko VM, Samarov EK. Application of the Kalman-Bucy filtering algorithm in power quality analysis problems. Electrotekhnicheskie i Informatsionnye Kompleksy i Sistemy. 2006;2(1):17-23. (In Russ.) EDN: IJVLTB