Conservative RCS Models for Tactical Simulation

Persson, Björn; Norsell, Martin

doi:10.1109/map.2015.2397151

Cited by 3 publications

(1 citation statement)

References 8 publications

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“…This work advances research on how to validate proposed motion models for the purpose of creating more realistic radar simulators. In addition, if conservative RCS models are to be created, it is beneficial to have a good understanding of the expected dynamics of the aircraft [25]. Simulators that consider the motion of the targets have been developed [22,26,27]; however experiments to verify the assumed motion models are required.…”

Section: Azmentioning

confidence: 99%

Empirical Study of Flight-Dynamic Influences on Radar Cross-Section Models

Persson

Bull

2016

Journal of Aircraft

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In this work, measurements and a method for analyzing flight-dynamic effects on radar cross-section models for aircraft are presented. Flight-dynamic effects need to be considered when designing combat aircraft and creating target models for radar simulators. The work is based on flight data from three different types of aircraft: Piper PA-28 Archer II, Boeing 737, and Saab JAS 39 Gripen. Using inertial navigation and global-positioning systems, the motions of the three aircraft are recorded in flight. From the data, aspect angles toward a radar station located in the extension of the intended flight path are generated using a simulator. It is found that the major contribution to perturbations in aspect angles is due to the rotational degrees of freedom and that bivariate normal distributions are a good candidate for approximating the uncertainty in aspect angles for all three aircraft types. It is also found that each rotational degree of freedom is close to a normal distribution but that the parameter values of the distribution vary with altitude and aircraft type. NomenclatureAz = azimuth aspect angle, deg a = major axis of confidence ellipse, deg b = minor axis of confidence ellipse, deg El = elevation aspect angle, deg E i = incident electric vector field, V∕m E s = scattered electric vector field, V∕m G = antenna gain h r = radar antenna height, m h t = target altitude, m P t = transmitted power, W R = range between radar and target, m R h = range to radar horizon, m R max = maximum detection range, m r e = effective radius of Earth, m S min = minimum detectable signal, W α = alpha risk θ = eigenvalue of Σ λ = radiation wavelength, m σ = radar cross-section, m 2 μ = mean value, deg ρ = correlation coefficient Σ = covariance matrix σ Az = azimuth standard deviation, deg σ El = elevation standard deviation, deg χ 2 2 α = upper αth percentile of chi-squared distribution with two degrees of freedom

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Section: Azmentioning

confidence: 99%

Empirical Study of Flight-Dynamic Influences on Radar Cross-Section Models

Persson

Bull

2016

Journal of Aircraft

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Estimating the Distribution of RCS Using Sparse Measured Samples

Väilä

Jylhä

Ruotsalainen

et al. 2018

2018 International Conference on Radar (RADAR)

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Scattering response modeling scheme based on combined neural network inspired by the equivalent scattering center

Yan

Wang

2022

Opt. Express

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A novel scheme is proposed in this paper to model the complex scattering pattern of radar target with a small training data set. By employing the ideal equivalent scattering center as transfer function, the frequency domain response can be represented by series of parameters so that the aspect and frequency domain dependency can be decoupled, and modeled, independently. In specific, neural network is employed to model the aspect dependency considering the complexity. To maintain the continuity of transformed parameters, a parameter extraction algorithm based on the Orthogonal Matching Pursuit is designed. With the same amount of training set, the proposed scheme exhibits a much better performance than the existing representative modeling techniques such as Geometrical Theory of Diffraction (GTD)-based model, the polynomial scattering center model and so on. At the same time, the training speed of the proposed model is also faster than those techniques.

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Conservative RCS Models for Tactical Simulation

Cited by 3 publications

References 8 publications

Empirical Study of Flight-Dynamic Influences on Radar Cross-Section Models

Empirical Study of Flight-Dynamic Influences on Radar Cross-Section Models

Estimating the Distribution of RCS Using Sparse Measured Samples

Scattering response modeling scheme based on combined neural network inspired by the equivalent scattering center

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