On the Equivalence of Hanning-Weighted and Overlapped Analysis Windows Using Different Window Sizes

Baggenstoss, Paul M.

doi:10.1109/lsp.2011.2175727

Cited by 10 publications

(8 citation statements)

References 5 publications

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“…In addition, authors applied Hannning window function with fourier transforms to detect moving object in a sea clutter. It was applied by Baggenstoss et al [50] who assessed different window sizes. The use of Guassian noise helped detecting pulses of unknown duration, while windowing enabled suppressing multiple radio frequency interference [51].…”

Section: Related Workmentioning

confidence: 99%

“…In this research paper initially the focus is made on augmenting aforesaid objectives. On the other hand, recalling the fact that the spectrogram technique by combining STFT in such a manner that it enables selection of the best FFT size for individual grid point in the frequency and the time plane can be a potential solution [50], we implement this model to achieve accurate small moving target detection in sea clutter. Towards this objective, the different STFT representations have been considered in such manner that it follows the concept of "equivalence".…”

Section: Problem Formulationmentioning

confidence: 99%

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Hanning Weighted Window Analysis Assisted Time-Series Analysis Model for Slow Moving Target Detection in Sea Clutter

Rajesh¹,

Udayarani²,

Jayaramaiah³

2020

International Journal of Engineering Research and Technology

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The exponential rise in maritime movement, security threats from up-surging terrorism and smuggling has alarmed academia-industries to develop more efficient method for target detection in coastal area. This task becomes more complex and intricate in case of small moving target in seaclutter. Amongst the major available approaches such as multiple-radar based methods, wavelet analysis methods, Doppler measurements, Fourier transforms, Short Term Fourier Transform (STFT) based techniques, STFT has been found more robust. The ability to perform simultaneous time and frequency analysis for time-series assessment enables STFT to be used in small target detection in sea clutter; however the inherent limitations such as improper Windowing, window-size, number of samples, overlapping conditions affect overall performance. Considering it as motivation, in this paper we have developed an efficient Hanning Weighted Window Function (HWWF) model to be used in conjunction with STFT to perform Hanning-Weighted Overlapped Time-Series Analysis (HWOTSA) to detect slow moving target detection in sea clutter. The use of orthonormal transformation also called rotation enabled Hanning Window Analysis to use suitable STFT parameters and statistical test across the windows to achieve better accuracy of the target detection. HWOTSA assisted STFT in conjunction with the Probability Distribution Function Projection (PPM) over extracted features enabled accurate slow moving target detection in sea clutter. The MATLAB based simulation affirmed that the proposed method enables accurate and swift (slow) moving target detection in sea clutter, without introducing higher computational overheads and complexities. The estimation of Doppler measurement based target velocity estimation armour proposed method to be used in real-time applications for swift decision making.

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Section: Related Workmentioning

confidence: 99%

Section: Problem Formulationmentioning

confidence: 99%

Hanning Weighted Window Analysis Assisted Time-Series Analysis Model for Slow Moving Target Detection in Sea Clutter

Rajesh¹,

Udayarani²,

Jayaramaiah³

2020

International Journal of Engineering Research and Technology

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“…Since is independent of for all , we bring the manifold integral to the inside, obtaining which from (13), gives the term independent of (21) which is just in (8). Using (14), we substitute into (20), and write in summation form (22) We can re-write this as , where…”

Section: E Entropy Maximizationmentioning

confidence: 99%

“…But, they will be exact PDF models from which data can be easily generated. Methods exist to extend our results to windowed data, but are outside the scope of this paper [22].…”

Section: B Circular Power Spectral Modelsmentioning

confidence: 99%

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Maximum Entropy PDF Design Using Feature Density Constraints: Applications in Signal Processing

Baggenstoss

2015

IEEE Trans. Signal Process.

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This paper revisits an existing method of constructing high-dimensional probability density functions (PDFs) based on the PDF at the output of a dimension-reducing feature transformation. We show how to modify the method so that it can provide the PDF with the highest entropy among all PDFs that generate the given low-dimensional PDF. The method is completely general and applies to arbitrary feature transformations. The chain-rule is described for multi-stage feature calculations typically used in signal processing. Examples are given including MFCC and auto-regressive features. Experimental verification of the results using simulated data is provided including a comparison with competing generative methods.

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Detecting Signals with Unknown Form: Energy Detectors

Abraham¹

2019

Modern Acoustics and Signal Processing

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On the Equivalence of Hanning-Weighted and Overlapped Analysis Windows Using Different Window Sizes

Cited by 10 publications

References 5 publications

Hanning Weighted Window Analysis Assisted Time-Series Analysis Model for Slow Moving Target Detection in Sea Clutter

Hanning Weighted Window Analysis Assisted Time-Series Analysis Model for Slow Moving Target Detection in Sea Clutter

Maximum Entropy PDF Design Using Feature Density Constraints: Applications in Signal Processing

Detecting Signals with Unknown Form: Energy Detectors

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