scholarly journals The adaptive notch filter with complex weights

2015 ◽  
pp. 21-26
Author(s):  
D. I. Popov
Keyword(s):  
Block Diagram ◽  
Notch Filter ◽  
Adaptive Algorithms ◽  
Batch Processing ◽  
Notch Filters ◽  
Spectral Correlation ◽  
Adaptive Notch Filter ◽  
Approximate Models ◽  
Adaptive Notch Filters

Considered the criteria and algorithms to adapt FIR notch filters to the unknown spectral-correlation characteristics of clutter. On the basis of approximate models obtained clutter stable computationally adaptive algorithms of filtration data interference. The block diagram of adaptive notch filters and sliding batch processing.

Adaptive Detection of Sinusoidal Signal Based on Adaptive Iir Notch Filter

2012 ◽  
Vol 482-484 ◽  
pp. 541-545
Author(s):  
Jin Chun Liu ◽  
Qi Wei He ◽  
Shi Jian Zhu
Keyword(s):  
Vibration Isolation ◽  
Notch Filter ◽  
Recursive Identification ◽  
Infinite Impulse Response ◽  
Notch Filters ◽  
Two Stage ◽  
Isolation System ◽  
Time Varying Frequency ◽  
Stage System ◽  
Adaptive Notch Filters

Adaptive tracking sinusoidal signals with time-varying frequency buried in white noise presents a great interest in engineering applications. A simple approach of application of adaptive notch filters (ANFs) in recursive identification was presented. The use of adaptive infinite impulse response (IIR) notch filters is exploited to detect the sinusoidal components in noise as far as the two-stage vibration isolation system. Computer simulations and experiments on real signals generated by the two-stage system vibration isolation demonstrate the advantage of this method in terms of estimation variance, convergence speed, and the capability of tracking the signals.

A Frequency Tracking Method Based on Improved Adaptive Notch Filter for Coriolis Mass Flowmeter

2011 ◽  
Vol 128-129 ◽  
pp. 450-456 ◽  
Author(s):  
Hui Yue Yang ◽  
Ya Qing Tu ◽  
Hai Tao Zhang
Keyword(s):  
Absolute Convergence ◽  
Notch Filter ◽  
Superior Performance ◽  
Time Varying ◽  
Frequency Tracking ◽  
Adaptive Notch Filter ◽  
Mass Flowmeter ◽  
Coriolis Mass Flowmeter ◽  
Convergence Problems ◽  
Adaptive Notch Filters

Adaptive notch filters (ANF) are known have non-absolute convergence problems which will lead to precision reduction in long-playing frequency tracking. In this paper, we propose an improved ANF based on Steiglitz-McBride method (SMM) for Coriolis mass flowmeter (CMF) whose frequency, amplitude and phase are time-varying based on the random walk model. An monitor is designed to monitor whether the frequency is estimated rightly or the ANF just filters noise. If the frequency of CMF’s signal is missed, we will modify the parameters and restart the ANF to resume the search for the correct frequency again. The particular algorithm of the improved ANF is also put forward. Simulations have verified the effectiveness of the presented method in tracking CMF’s frequency, which shows superior performance comparing to the primary SMM based ANF.

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