Measurement for radar target identification using short-time matrix pencil method

Kheawprae, Feaveya; Boonpoonga, Akkarat; Sangchai, W.

doi:10.1109/cama.2015.7428184

Cited by 5 publications

(2 citation statements)

References 3 publications

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“…Secondly, predictions in the high-frequency band have been made using three prediction theories, such as the Prony method [21][22][23][24][25][26][27][28], MPM [29][30][31][32][33][34][35][36], and Rational Function based on the indirect calculation method in order to verify the reliability and validity of the prediction theories. In addition, three representative military aircraft were applied to confirm the possibility and validity of the RCS measurement results according to the aircraft type, and through this, a mutual comparison of the three theories was performed.…”

Section: Object Rcs [M 2 ]mentioning

confidence: 99%

RCS Prediction Using Prony Method in High-Frequency Band for Military Aircraft Models

Ahn

Koh

2022

Aerospace

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Obtaining Radar Cross Section (RCS) data, one of the essential parameters for aircraft design, generally takes a lot of time and cost. Measurement time and accuracy of measurement results may be affected depending on the RCS measurement method and environment. When it comes to the RCS measurement method, the direct approach, which measures RCS on a real item, is more accurate than the indirect approach, which is implemented through simulation. However, in consideration of balancing accuracy, time and cost, the indirect approach is more generally used due to its efficiency. In this paper, in order to find an optimized method for more improved prediction results of indirect approach in the high-frequency band, three prediction methods are proposed: the Prony method, the Matrix pencil method (MPM) and the Rational Function method. It is confirmed that the RCS prediction result utilizing the Prony method in the high-frequency band has the minimum error in the case of Prony and MPM Methods, which have not been utilized for RCS prediction in the high-frequency band, and the Rational function method with currently applicable cases are employed. The prediction methods are, respectively, applied to a model based on three military aircraft models such as Jet Plane, F-117 and Transport Plane, and its simulation is performed under identical conditions. The original data and the extrapolated data obtained from the methods are compared at a certain angle for each model, and the errors between the extrapolated data are also compared in order to verify the efficacy of the prediction methods.

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Section: Object Rcs [M 2 ]mentioning

confidence: 99%

RCS Prediction Using Prony Method in High-Frequency Band for Military Aircraft Models

Ahn

Koh

2022

Aerospace

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“…The complex natural frequency, called a pole, which is extracted from the late‐time response, is a tool for aspect‐independent target identification. There are many published works dealing with extracting poles from the scattering response (see examples in Bannawat et al, ; Boonpoonga, ; Chantasan et al, ; Chantasen et al, ; Kheawprae et al, ; Yochanang et al, ). The matrix pencil method (MPM) proposed in Sarkar and Pereira () to extract poles has drawn considerable attention because of its performance in dealing with noise.…”

Section: Introductionmentioning

confidence: 99%

Automatic Detection and Classification of Buried Objects Using Ground‐Penetrating Radar for Counter‐Improvised Explosive Devices

et al. 2018

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In this paper, a technique that can automatically detect and classify objects buried under the ground is proposed. The technique employs a ground‐penetrating radar that transmits electromagnetic waves in order to strike the objects and then receives the backscattering electromagnetic wave to perform signal processing. This signal processing is divided into four main steps as follows. First, preprocessing is used to reduce the clutter due to the effect of the media layer interface. Second, the late time of the scattering signal is estimated using a simple cross correlation. Third, a few successive poles are extracted from the scattering response at the estimated late time by using the short‐time matrix pencil method. Finally, the extracted poles are fed for object classification with different constitutions and/or shapes using a support vector machine. Simulations according to the practical situation in three southern provinces of Thailand to counter the improvised explosive devices were set up. The performance of the proposed technique was evaluated. The simulation results showed that the proposed technique can efficiently detect and classify buried objects for counter‐improvised explosive device operations in the military.

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Singularity Expansion Method in Radar Multimodal Signal Processing and Antenna Characterization

Bhattacharyya¹,

Siddiqui

2021

Intelligent Multi‐modal Data Processing

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Measurement for radar target identification using short-time matrix pencil method

Cited by 5 publications

References 3 publications

RCS Prediction Using Prony Method in High-Frequency Band for Military Aircraft Models

RCS Prediction Using Prony Method in High-Frequency Band for Military Aircraft Models

Automatic Detection and Classification of Buried Objects Using Ground‐Penetrating Radar for Counter‐Improvised Explosive Devices

Singularity Expansion Method in Radar Multimodal Signal Processing and Antenna Characterization

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