MST Radar Signal Processing Using Cepstral Thresholding

Reddy, T. Sreenivasulu; Reddy, G. Ramachandra

doi:10.1109/tgrs.2009.2039937

Cited by 18 publications

(8 citation statements)

References 15 publications

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“…There are many methods for radar signal processing including the application of single method [87,88] and the combination of multidisciplinary and multimethod (as shown in Figure 11). In order to eliminate the subjectivity of feature extraction and improve the accuracy of radar signal sorting, recognition, and processing, effective multidisciplinary and multimethods are needed to perform signal processing work [89][90][91].…”

Section: Radar Signal Processing Technologymentioning

confidence: 99%

“…Multi-disciplinary and multi-method Single processing method DVB-T passive RS [90] Chaotic RS [91] Signal type UWB SIRE [92] MST [93] Riemannian medians [94] WFS A [89] Signal type…”

Section: Radar Signal Processing Technologymentioning

confidence: 99%

“…Chaotic RS [90] UWB SIRE [91] MST [92] Riemannian medians [93] WFS A [89] Figure 11: RS processing types of single and the combination of multidisciplinary and multimethod.…”

Section: Dvb-t Passive Rs [90]mentioning

confidence: 99%

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Processing Technology Based on Radar Signal Design and Classification

Zhang

Zhan

2020

International Journal of Aerospace Engineering

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It is well known that the application of radar is becoming more and more popular with the development of the signal technology progress. This paper lists the current radar signal research, the technical progress achieved, and the existing limitations. According to radar signal respective characteristics, the design and classification of the radar signal are introduced to reflect signal’s differences and advantages. The multidisciplinary processing technology of the radar signal is classified and compared in details referring to adaptive radar signal process, pulse signal management, digital filtering signal mode, and Doppler method. The transmission process of radar signal is summarized, including the transmission steps of radar signal, the factors affecting radar signal transmission, and radar information screening. The design method of radar signal and the corresponding signal characteristics are compared in terms of performance improvement. Radar signal classification method and related influencing factors are also contrasted and narrated. Radar signal processing technology is described in detail including multidisciplinary technology synthesis. Adaptive radar signal process, pulse compression management, and digital filtering Doppler method are very effective technical means, which has its own unique advantages. At last, the future research trends and challenges of technologies of the radar signals are proposed. The conclusions obtained are beneficial to promote the further promotion applications both in theory and practice. The study work of this paper will be useful for choosing more reasonable radar signal processing technology methods.

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Section: Radar Signal Processing Technologymentioning

confidence: 99%

“…Multi-disciplinary and multi-method Single processing method DVB-T passive RS [90] Chaotic RS [91] Signal type UWB SIRE [92] MST [93] Riemannian medians [94] WFS A [89] Signal type…”

Section: Radar Signal Processing Technologymentioning

confidence: 99%

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Processing Technology Based on Radar Signal Design and Classification

Zhang

Zhan

2020

International Journal of Aerospace Engineering

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“…Since the lower stratosphere extends from 10 to 20 km above the earth's surface, any spectrum estimating algorithm is expected to give good results in this particular range. There arises a need to go for a better functioning spectrum estimation method, especially at the height range of 14-17 km, as the existing methods [3][4][5][6] at this height fail to estimate the power spectrum accurately. Hence, semiparametric techniques can be focused on to improve the spectral estimation accuracy even for ill-conditioned data.…”

Section: Introductionmentioning

confidence: 99%

Fast implementation of sparse iterative covariance-based estimation for processing MST radar data

Raju

Reddy

2019

SN Appl. Sci.

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Doppler estimation is an essential problem for the mesosphere-stratosphere-troposphere (MST) radar data for estimation of atmospheric parameters. The Doppler is estimated by computing the power spectral density using either parametric or non-parametric method. A recent class of spectral estimation technique referred as Sparse Iterative Covariance Based Estimation (SPICE) is introduced in literature. SPICE is a sound, user-parameter free, good resolution, iterative and globally convergent method which exhibits the enhanced results than the current spectral estimation methods, at the high computational cost. This letter presents the fast implementation of the SPICE algorithm for the MST radar data and the estimation of various wind parameters at a lesser computational time and is validated with the radiosonde data.

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“…Bi-spectral estimation [2] and Multi taper spectral estimation [3] is used to radar signal, which include broadened spectral peak and high computational cost respectively. Other algorithms like cepstral thresholding [4], wavelet-based denoising [5] and PCA approach [6] are also applied to spectrum estimation of the MST data. MELT algorithm is based on robust covariance estimation is explained in [7], and it is found to give improved results in both simulation and radar signals.…”

Section: Introductionmentioning

confidence: 99%

Spectral Analysis of MST Radar Signal using Maximum Likelihood Estimation Algorithm

Latha,

Chandraiah,

Varadarajan

et al. 2019

IJEAT

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In this work, we propose Maximum likelihood estimation of low- rank Toeplitz covariance matrix (MELT) with reduced complexity algorithm for computing the power spectral density of mesosphere-stratosphere-troposphere (MST) radar data. MELT is designed based on the method of majorization-minimization and it is an iterative algorithm to update the powers in each successive step. We tested MELT algorithm for complex signal, which contain multiple frequency components in existence of different noise conditions. For simulated complex data, it can be seen that MELT works much better for low Signal to Noise Ratio (SNR) conditions and also effectively detects the frequency components with a fine resolution in the existence with high noise impact. At last, MELT algorithm is applied to the radar data received from MST radar established at National Atmospheric Research laboratory (NARL), Gadhanki. MELT algorithm estimates the accurate Doppler spectra and thus in turn, estimate the wind parameters using Doppler profiles. For the purpose of validation, the obtained radar results through MELT are compared with the Global Positioning System (GPS) radiosonde.

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MST Radar Signal Processing Using Cepstral Thresholding

Cited by 18 publications

References 15 publications

Processing Technology Based on Radar Signal Design and Classification

Processing Technology Based on Radar Signal Design and Classification

Fast implementation of sparse iterative covariance-based estimation for processing MST radar data

Spectral Analysis of MST Radar Signal using Maximum Likelihood Estimation Algorithm

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