Spectral analysis comparisons of Fourier-theory-based methods and minimum variance (Capon) methods

Garbanzo-Salas, Marcial; Hocking, W. K.

doi:10.1016/j.jastp.2015.07.003

Cited by 4 publications

(3 citation statements)

References 11 publications

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“…Kouemou and Opitz [7] introduced a wavelet-based feature analysis combined with Hidden Markov Models (HMM) to classify real radar signals into predefined categories. Spectral analysis [8] is used by Garbanzo-Salas and Hocking [9] for detecting small objects from harmonic pulse radar data. The use of online bootstrapping machine learning tools to improve target detection rate of radar signals is also one major research area [10].…”

Section: Related Workmentioning

confidence: 99%

Stacked Autoencoders for Outlier Detection in Over-the-Horizon Radar Signals

Protopapadakis

Voulodimos

Doulamis

et al. 2017

Computational Intelligence and Neuroscience

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Detection of outliers in radar signals is a considerable challenge in maritime surveillance applications. High-Frequency Surface-Wave (HFSW) radars have attracted significant interest as potential tools for long-range target identification and outlier detection at over-the-horizon (OTH) distances. However, a number of disadvantages, such as their low spatial resolution and presence of clutter, have a negative impact on their accuracy. In this paper, we explore the applicability of deep learning techniques for detecting deviations from the norm in behavioral patterns of vessels (outliers) as they are tracked from an OTH radar. The proposed methodology exploits the nonlinear mapping capabilities of deep stacked autoencoders in combination with density-based clustering. A comparative experimental evaluation of the approach shows promising results in terms of the proposed methodology's performance.

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Section: Related Workmentioning

confidence: 99%

Stacked Autoencoders for Outlier Detection in Over-the-Horizon Radar Signals

Protopapadakis

Voulodimos

Doulamis

et al. 2017

Computational Intelligence and Neuroscience

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“…When the number of carrier frequencies used for RIM was not larger than the number of distinct spectral lines in the signal (e.g., distinct moving layers or targets with different velocities), the Capon method could not resolve the distinct spectral lines effectively and might miss the weaker ones. Moreover, the Capon method was not superior to the fast Fourier transform for a continuous spectrum (Li and Stoica, 1996;Garbanzo-Salas and Hocking, 2015). In practical operation for the atmosphere, however, the number of carrier frequencies is limited, which will be discussed in Sect.…”

Section: Range Imaging Technique Of the Chung-li Vhf Radarmentioning

confidence: 99%

Evaluation of multifrequency range imaging technique implemented on the Chung–Li VHF atmospheric radar

Chen

Tsai

et al. 2016

Atmos. Meas. Tech.

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Abstract. The multifrequency range imaging technique (RIM) has been implemented on the Chung-Li VHF array radar since 2008 after its renovation. This study made a more complete examination and evaluation of the RIM technique to facilitate the performance of the radar for atmospheric studies. RIM experiments with various radar parameters such as pulse length, pulse shape, receiver bandwidth, transmitter frequency set, and so on were conducted. The radar data employed for the study were collected from 2008 to 2013. It has been shown that two factors, the range/time delay of the signal traveling in the media and the standard deviation of Gaussian-shaped range-weighting function, play crucial roles in ameliorating the RIM-produced brightness (or power distribution); the two factors are associated with some radar parameters and system characteristics. The range/time delay of the signal was found to increase with time; moreover, it was slightly different for the echoes from the atmosphere with and without the presence of significant precipitation. A procedure of point-by-point correction of range/time delay was thus executed for the presence of precipitation to minimize the bogus brightness discontinuity at range gate boundaries. With the RIM technique, the Chung-Li VHF radar demonstrates its first successful observation of double-layer structures as well as their temporal and spatial variations with time.

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“…[] applied Capon's method to radar study of clear‐air turbulence and precipitation events using the MU radar in Japan demonstrating the robustness and high‐resolution qualities of Capon's method relative to the FFT method. On the other hand, Garbanzo‐Salas and Hocking [] pointed out several concerns regarding the effect of filter size, resolution performance, and computing power of Capon's method based on the comparison with FFT approach on four different scenarios. The maximum entropy (ME) method was proposed by Ables [] and has been applied to image reconstruction in various areas such as aperture synthesis in radio astronomy and X‐ray imaging.…”

Section: Introductionmentioning

confidence: 99%

Coherent radar imaging based on compressed sensing

2015

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High-resolution radar images in the horizontal spatial domain generally require a large number of different baselines that usually come with considerable cost. In this paper, aspects of compressed sensing (CS) are introduced to coherent radar imaging. We propose a single CS-based formalism that enables the full three-dimensional (3-D)-range, Doppler frequency, and horizontal spatial (represented by the direction cosines) domain-imaging. This new method can not only reduce the system costs and decrease the needed number of baselines by enabling spatial sparse sampling but also achieve high resolution in the range, Doppler frequency, and horizontal space dimensions. Using an assumption of point targets, a 3-D radar signal model for imaging has been derived. By comparing numerical simulations with the fast Fourier transform and maximum entropy methods at different signal-to-noise ratios, we demonstrate that the CS method can provide better performance in resolution and detectability given comparatively few available measurements relative to the number required by Nyquist-Shannon sampling criterion. These techniques are being applied to radar meteor observations. Interferometric imaging has been introduced to radio and radar observations for decades in the fields of astronomy, meteorology, atmosphere/ionosphere observations, plasma physics, and so on [Marouf et al., 1982;Kunitsyn and Tereshchenko, 1992;Igarashi et al., 2000;Pavelyev et al., 2002]. Interferometry was first used at the Jicamarca Radio Observatory for measuring the inclination of the geomagnetic field [Woodman, 1971]. Since then, it has been successfully applied to study ionospheric plasma irregularity phenomena [Farley et al., 1981;Kudeki and Stitt, 1987;Hysell, 1996]. It is a practical way to simultaneously achieve both fine spatial and temporal resolutions. Its mathematical basis is the Fourier transform relationship between the spatial correlation of the electromagnetic fields scattered from targets-visibility measurements-and the angular brightness ZHU ET AL.COHERENT RADAR IMAGING Key Points:• Discrete linear radar signal model for holography is proposed • Aspects of compressed sensing are introduced to holography • Outstanding performance of compressed sensing is proved

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Spectral analysis comparisons of Fourier-theory-based methods and minimum variance (Capon) methods

Cited by 4 publications

References 11 publications

Stacked Autoencoders for Outlier Detection in Over-the-Horizon Radar Signals

Stacked Autoencoders for Outlier Detection in Over-the-Horizon Radar Signals

Evaluation of multifrequency range imaging technique implemented on the Chung–Li VHF atmospheric radar

Coherent radar imaging based on compressed sensing

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