High-Resolution Spectrum Estimation

2016 ◽  
pp. 325-373
Keyword(s):  
High Resolution ◽  
High Resolution Spectrum ◽  
Spectrum Estimation

scholarly journals High-Resolution Spectral Estimation of HF Radar Data for Current Measurement Applications

2015 ◽  
Vol 32 (8) ◽  
pp. 1515-1525 ◽  
Author(s):  
Wei Wang ◽  
Eric Gill
Keyword(s):  
High Resolution ◽  
Spectral Estimation ◽  
Surface Current ◽  
Rayleigh Distribution ◽  
Radar Data ◽  
Hf Radar ◽  
High Resolution Spectrum ◽  
Spectrum Estimation ◽  
Centroid Method ◽  
Domain Transformation

AbstractThis paper presents a comparative study of high-resolution methods for high-frequency radar current mapping. A z-domain transformation and auxiliary z-domain manipulation of the autoregressive method is proposed for this comparison. A Weibull distribution test is recommended to justify the Rayleigh distribution of the sea clutter for quality control. Upon the power spectrum estimation, a conventional centroid method and a new symmetric-peak-sum method for the identification of current Doppler shift are proposed as another comparison. HF radar data were collected over the period from November 2012 to August 2013 at Placentia Bay, Newfoundland, Canada, and were compared with measurements from an acoustic Doppler current meter. This comparison is used to study the utility of high-resolution spectrum estimation and Bragg identification methods for surface current mapping. Results show promising use of these methods in different current scenarios and suggest combined applications to improve accuracy.

scholarly journals High Resolution and Fast Processing of Spectral Reconstruction in Fourier Transform Imaging Spectroscopy

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4159
Author(s):  
Weikang Zhang ◽  
Desheng Wen ◽  
Zongxi Song ◽  
Xin Wei ◽  
Gang Liu ◽  
...  
Keyword(s):  
Fourier Transform ◽  
High Resolution ◽  
Parallel Algorithm ◽  
Imaging Spectroscopy ◽  
Operation Time ◽  
High Resolution Spectrum ◽  
Processing Unit ◽  
Spectrum Estimation ◽  
Parallel Solution ◽  
Central Processing

High-resolution spectrum estimation has continually attracted great attention in spectrum reconstruction based on Fourier transform imaging spectroscopy (FTIS). In this paper, a parallel solution for interference data processing using high-resolution spectrum estimation is proposed to reconstruct the spectrum in a fast high-resolution way. In batch processing, we use high-performance parallel-computing on the graphics processing unit (GPU) for higher efficiency and lower operation time. In addition, a parallel processing mechanism is designed for our parallel algorithm to obtain higher performance. At the same time, other solving algorithms for the modern spectrum estimation model are introduced for discussion and comparison. We compare traditional high-resolution solving algorithms running on the central processing unit (CPU) and the parallel algorithm on the GPU for processing the interferogram. The experimental results illustrate that runtime is reduced by about 70% using our parallel solution, and the GPU has a great advantage in processing large data and accelerating applications.

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