Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
7125007 | Measurement | 2014 | 10 Pages |
Abstract
A nonlinear adaptive noise induced algorithm with nonlinear weights was proposed to extract rigid body deceleration during penetration events; it has 3rd-order nonlinear weight, which ensures deceleration curve is smooth everywhere (not only continuous) and avoids sharp points (crucial for targets detection). In addition, an autocorrelation algorithm was improved by applying moving window method to be compared with the proposed nonlinear adaptive algorithm. By calculating penetration depth and Power Spectrum Density (PSD) of 4 deceleration time series, we show that the nonlinear adaptive algorithm more effectively reduces noise in deceleration for striking velocities between 538 and 800 m/s compared with Adaptive Paйta Criterion, moving window autocorrelation and wavelet algorithms. It is further shown that the proposed adaptive algorithm is of the same order as the other 3 methods in terms of computational complexity.
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Physical Sciences and Engineering
Engineering
Control and Systems Engineering
Authors
Zongbao Liu, Shiqiao Gao, Haipeng Liu, Dongmei Zhang, Lei He,