Discrimination of active false targets in multistatic radar using spatial scattering properties

Zhao, Shuang; Zhang, Linrang; Zhou, Yu; Liu, Nan; Liu, Jieyi

doi:10.1049/iet-rsn.2014.0147

Cited by 35 publications

(29 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…From the signal model, the signal‐to‐noise ratio (SNR) and the jamming‐to‐noise ratio (JNR) can be obtained by

SNR = \frac{{(||, α)}^{2}}{σ_{n}^{2}},

JNR = \frac{{(||, β)}^{2}}{σ_{n}^{2}} .

However, considering the implementation of deception jamming does not depend on the power [1], SNR and JNR are assumed the same and defined as target‐to‐noise ratio (TNR) [30]

TNR = \frac{{(||, α)}^{2}}{σ_{n}^{2}} = \frac{{|β|}^{2}}{σ_{n}^{2}} .

To analyse the ultimate localisation performance under different conditions, root mean square error (RMSE) is utilised

RMSE = \sqrt{\frac{1}{N_{mc}} \sum_{i = 1}^{N_{mc}} false[{()(, {\overset{false^}{x}}_{p, i} - x_{p})}^{2} + {()(, {\overset{false^}{y}}_{p, i} - y_{p})}^{2} false]},

where

N_{mc}

denotes Monte Carlo simulation times,

()(, x_{p}, y_{p})

is the exact coordinate of the physical target, and

()(, {\overset{false^}{x}}_{p, i}, {\overset{false^}{y}}_{p, i})

denotes the estimated coordinate of the physical target.…”

Section: Numerical Resultsmentioning

confidence: 99%

“…In [27], a suppression method against range–velocity joint deception jamming has been devised, which is based on the diversities of target and the consistency (the same source) of false target. According to the spatial diversity [28, 29], discrimination algorithms have been proposed, where correlation test is performed in complete non‐correlated system model [30] and in partial correlated system model [31] by directly using the echoes from different receivers. However, the performance will deteriorate severely for the lack of enough pulse number.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Joint range–velocity deception jamming suppression for SIMO radar

Huang

Cui

et al. 2019

IET Radar, Sonar & Navigation

View full text Add to dashboard Cite

“…From the signal model, the signal‐to‐noise ratio (SNR) and the jamming‐to‐noise ratio (JNR) can be obtained by

SNR = \frac{{(||, α)}^{2}}{σ_{n}^{2}},

JNR = \frac{{(||, β)}^{2}}{σ_{n}^{2}} .

However, considering the implementation of deception jamming does not depend on the power [1], SNR and JNR are assumed the same and defined as target‐to‐noise ratio (TNR) [30]

TNR = \frac{{(||, α)}^{2}}{σ_{n}^{2}} = \frac{{|β|}^{2}}{σ_{n}^{2}} .

To analyse the ultimate localisation performance under different conditions, root mean square error (RMSE) is utilised

RMSE = \sqrt{\frac{1}{N_{mc}} \sum_{i = 1}^{N_{mc}} false[{()(, {\overset{false^}{x}}_{p, i} - x_{p})}^{2} + {()(, {\overset{false^}{y}}_{p, i} - y_{p})}^{2} false]},

where

N_{mc}

denotes Monte Carlo simulation times,

()(, x_{p}, y_{p})

is the exact coordinate of the physical target, and

()(, {\overset{false^}{x}}_{p, i}, {\overset{false^}{y}}_{p, i})

denotes the estimated coordinate of the physical target.…”

Section: Numerical Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Joint range–velocity deception jamming suppression for SIMO radar

Huang

Cui

et al. 2019

IET Radar, Sonar & Navigation

View full text Add to dashboard Cite

“…However, this method cannot fully explore the amplitude and phase information of receiving signals. In [12–14], deception jamming is discriminated according to the difference between real target echoes and deceptive jamming in spatial scattering properties for distributed radar. In [15], a hierarchical clustering analysis method was utilised to discriminate deceptive targets in a defined amplitude ratio feature space.…”

Section: Introductionmentioning

confidence: 99%

Mainlobe jamming suppression for distributed radar via joint blind source separation

Cui

Kong

2019

IET Radar, Sonar & Navigation

View full text Add to dashboard Cite

“…Radar network system employing multiple, widely distributed stations have been shown to offer significant advantages over monostatic radar in various aspects of radar applications, such as moving target detection, direction finding and target localization, which poses a great threat to the stealth airplane, low altitude attack, and anti-radiation missile [1]- [5]. Radar phantom track generation by a group of cooperating ECAVs has received increased attention in the recent past.…”

Section: Introductionmentioning

confidence: 99%

A Three-Dimensional Phantom Track Generation for Radar Network Deception (January 2019)

Liu

2019

IEEE Access

View full text Add to dashboard Cite

One important issue when multiple cooperating electronic combat air vehicles (ECAVs) are used to generate phantom radar tracks in a radar network is the position inaccuracy, which is the fundamental reasons for the difference between a phantom track and a real track. According to this difference, a radar network can recognize the phantom track from the real target track. In order to solve this problem, first, two kinds of phantom tracks in three-dimensional space are developed from the generalized kinematic framework. Then, the effect of the inaccuracies of radar position and ECAVs position to the phantom track is considered in detail. Finally, the beam rider guidance method is used to compensate the track deviation. The scenario of phantom track generation and the influence factors of the maximum position deviation is simulated and analyzed particularly. The simulation results show that the deviation compensation method can reduce the recognition rate of the phantom track effectively. INDEX TERMS Electronic combat air vehicles, radar network, phantom tracks, deviation compensation.

show abstract

Discrimination of active false targets in multistatic radar using spatial scattering properties

Cited by 35 publications

References 18 publications

Joint range–velocity deception jamming suppression for SIMO radar

Joint range–velocity deception jamming suppression for SIMO radar

Mainlobe jamming suppression for distributed radar via joint blind source separation

A Three-Dimensional Phantom Track Generation for Radar Network Deception (January 2019)

Contact Info

Product

Resources

About