Performance Comparison of Blackman, Bartlett, Hanning, and Kaiser Window for Radar Digital Signal Processing

2019 ◽  
Author(s):  
Sulistyaningsih ◽  
Prasetyo Putranto ◽  
Taufiq qurrachman ◽  
Winy Desvasari ◽  
Pamungkas Daud ◽  
...  
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Digital Signal ◽  
Performance Comparison ◽  
Kaiser Window

scholarly journals Proposing a new variable window for better side lobe reduction

2019 ◽  
Vol 8 (9) ◽  
pp. 1107-1112
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Power Loss ◽  
Finite Impulse Response ◽  
Variable Parameter ◽  
Digital Signal ◽  
Side Lobe ◽  
Fir Filter ◽  
Side Lobe Level ◽  
Kaiser Window

Digital signal processing is most widely used to process the signal. In digital signal processing filters are used to remove some unwanted constituents from aspired signal. Windowing is a scheme of finite impulse response filters. Present paper proposes a new versatile window function. It has two variable parameters first one is window span N and another changeable parameter is r. when the value of variable parameter r increases width of major lobe of window also increases with better side lobe reduction and vice versa. Gaussian window and Kaiser window are the well-known variable windows. This paper shows that the proposed window has more desirable results in comparison of Gaussian and Kaiser window with low power loss and better side lobe reduction. To achieve minimum power loss peak side lobe level should have to minimum. Proposed window has low peak side lobe level (-17.681dB) in comparison of Gaussian (-11.836dB) and Kaiser window (-6.9704dB). Proposed work shows that the proposed window has finer spectral characteristic then Gaussian and Kaiser window. FIR filter formed by applying proposed window has narrow -3dB bandwidth (2π×0.320 rad/sample) corresponding to FIR filter formed by using Gaussian and Kaiser window. Ripple ratio of FIR filter plotted by applying proposed window (-144.321dB) is less corresponding to FIR filter delineated by using Gaussian and Kaiser which indicates that the proposed window will give better side lobe rejection and reduce the aliasing problem. In the biomedical field noise present in ECG signal can also reduce by using proposed window.

scholarly journals Performance comparison of DML, EML and MZM in dispersion-unmanaged short reach transmissions with digital signal processing

2018 ◽  
Vol 26 (26) ◽  
pp. 34288 ◽  
Author(s):  
Kuo Zhang ◽  
Qunbi Zhuge ◽  
Haiyun Xin ◽  
Weisheng Hu ◽  
David V. Plant
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Digital Signal ◽  
Performance Comparison

Method of estimation of hidden correlation of narrowband noise signals

2019 ◽  
pp. 34-39 ◽  
Author(s):  
E.I. Chernov ◽  
N.E. Sobolev ◽  
A.A. Bondarchuk ◽  
L.E. Aristarhova
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
New Technology ◽  
Digital Signal ◽  
Measuring Instruments ◽  
Central Frequency ◽  
Pearson Criterion ◽  
Useful Signal ◽  
Band Limited ◽  
Narrowband Noise

The concept of hidden correlation of noise signals is introduced. The existence of a hidden correlation between narrowband noise signals isolated simultaneously from broadband band-limited noise is theoretically proved. A method for estimating the latent correlation of narrowband noise signals has been developed and experimentally investigated. As a result of the experiment, where a time frag ent of band-limited noise, the basis of which is shot noise, is used as the studied signal, it is established: when applying the Pearson criterion, there is practically no correlation between the signal at the Central frequency and the sum of signals at mirror frequencies; when applying the proposed method for the analysis of the same signals, a strong hidden correlation is found. The proposed method is useful for researchers, engineers and metrologists engaged in digital signal processing, as well as developers of measuring instruments using a new technology for isolating a useful signal from noise – the method of mirror noise images.

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