Improving the response of a wheel speed sensor using an adaptive line enhancer

Measurement: Journal of the International Measurement Confederation

Volumn 33, Issue 3, 2003, Pages 229-240

  Hernández, Wilmar ^a  

^a UNIVERSIDAD POLITÉCNICA DE MADRID   (Spain)

Author keywords

Adaptive line enhancer; Fast LMS adaptive filter; Wheel speed sensor

Indexed keywords

ALGORITHMS; BRAKING; FREQUENCY DOMAIN ANALYSIS; NOTCH FILTERS; SENSORS; SIGNAL INTERFERENCE; SIGNAL TO NOISE RATIO; VEHICLE WHEELS;

WHEEL SPEED SENSORS;

SPEED CONTROL;

EID: 0037395838     PISSN: 02632241     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0263-2241(02)00077-5     Document Type: Article

References (25)

1. Elgar P. Sensors for Measurement and Control. 1998;Addison-Wesley Longman.
2. Herceg E.E. Handbook of Measurement and Control. 1972;Schaevitz Engineering, Camden, NJ.
3. Hernández W. Improving the response of an accelerometer by using optimal filtering. Sensors Actuators A. 88:2001;198-208.
4. Hernández W. Improving the response of several accelerometers used in a car under performance tests by using Kalman filtering. Sensors. 1:2001;38-52.
5. Kailtah T. A view of three decades of linear filtering. IEEE Trans. Inf. Theory. IT-20:(2):1974;146-181.
6. Widrow B., Glover J.R. Jr., McCool J.M., Kaunitz J., Williams C.S., Hear R.H., Zeidler J.R., Dong E. Jr., Goodlin R.C. Adaptive noise canceling: principles and applications. Proc. IEEE. 63:(12):1975;1692-1716.
7. Widrow B., Stearns S.D. Adaptive Signal Processing. 1985;Prentice-Hall, Englewood Cliffs, NJ.
8. Haykin S. Adaptive Filter Theory. 3rd Edition: 1996;Prentice-Hall, London.
9. Ferrara E.R. Jr. Fast implementation of LMS adaptive filters. IEEE Trans. Acoustic Speech Signal Processing. ASSP-28:1980;474-475.
10. Clark G.A., Mitra S.K., Parker S.R. Block implementation of adaptive digital filters. IEEE Trans. Circuits Syst. CAS-28:1981;584-592.
11. Clark G.A., Parker S.R., Mitra S.K. A unified approach to time- and frequency-domain realization of FIR adaptive digital filters. IEEE Trans. Acoustic Speech Signal Processing. ASSP-31:1983;1073-1083.
12. Ferrara E.R. Jr. Frequency-domain adaptive filtering. Cowan C.F.N., Grant P.M. Adaptive Filters. 1985;145-179 Prentice-Hall, Englewood Cliffs, NJ.
13. Shynk J.J. Frequency-domain and multirate adaptive filtering. IEEE Signal Processing Mag. 9:(1):1992;14-37.
14. Yoganandam Y., Reddy V.U., Kailath T. Performance analysis of the adaptive line enhancer for sinusoidal signals in broad-band noise. IEEE Trans. Acoustic Speech Signal Processing. ASSP-36:(11):1988;1749-1757.
15. Zeidler J.R. Performance analysis of LMS adaptive prediction filters. Proc. IEEE. 78:(12):1990;1781-1806.
16. Zames G. Feedback and optimal sensitivity: model reference transformation, multiplicative seminorms, and approximate inverses. IEEE Trans. Automatic Control. AC-26:(2):1981;301-320.
17. Zames G., Francis B.A. Feedback, minimax sensitivity, and optimal robustness. IEEE Trans. Automatic Control. AC-28:(5):1983;585-601.
18. Zhou K., Doyle J.C., Glover K. Robust and Optimal Control. 1996;Prentice-Hall, Upper Saddle River, NJ.
19. Roy S., Shynk J.J. Analysis of the momentum LMS algorithm. IEEE Trans. Acoustic Speech Signal Processing. ASSP-38:(12):1990;2088-2098.
20. Rupp M. The behavior of LMS and NLMS algorithms in the presence of spherically invariant processes. IEEE Trans. Signal Processing. 41:(3):1993;1149-1160.
21. Slock D.T.M. On the convergence behavior of the LMS and the normalized LMS algorithms. IEEE Trans. Signal Processing. 45:(12):1993;2811-2825.
22. Rupp M. Bursting in the LMS algorithm. IEEE Trans. Signal Processing. 43:(10):1995;2414-2417.
23. ∞ optimality of the LMS algorithm. IEEE Trans. Signal Processing. 44:(2):1996;267-280.
24. Solo V. The stability of the LMS. IEEE Trans. Signal Processing. 45:(12):1997;3017-3026.
25. Aparicio F., Vera C., Díaz V. Teoría de los Vehículos Automóviles. 1995;Sección de Publicaciones de la ETSII-UPM, Madrid.