A radar waveform bandwidth selection strategy for wideband tracking

Chang, Shaoqiang; Zhang, Honggang; Li, Teng; Liu, Quanhua; Zheng, Li

doi:10.1007/s11432-018-9736-9

Cited by 2 publications

(4 citation statements)

References 3 publications

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“…Theoretically, the use of this training data helps avoid the signal cancellation problems challenging traditional adaptive filter regimes. Using the training data, the covariance matrix can be estimated by Equation (17). (17) In the equation, insufficient sampling points are yielded by jamming recognition, the resulting covariance matrix may not be very accurate, and the anti-jamming performance may not be sufficient as a consequence.…”

Section: B Jamming Suppression Based On Iaamentioning

confidence: 99%

“…Using the training data, the covariance matrix can be estimated by Equation (17). (17) In the equation, insufficient sampling points are yielded by jamming recognition, the resulting covariance matrix may not be very accurate, and the anti-jamming performance may not be sufficient as a consequence. Traditionally, a covariance matrix is reconstructed by DOA estimation using a Capon spatial spectrum [29]- [31].…”

Section: B Jamming Suppression Based On Iaamentioning

confidence: 99%

“…In terms of waveform design, anti-jamming can be achieved by designing special waveforms to destroy the output continuity of the Doppler frequency of jamming [17]. In addition, polarization discrimination technology has also become an important method to suppress interruptedsampling repeater jamming [18].…”

Section: Introductionmentioning

confidence: 99%

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Suppression Method for Main-Lobe Interrupted Sampling Repeater Jamming in Distributed Radar

Chen

Zhang

et al. 2020

IEEE Access

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Main-lobe interrupted-sampling repeater jamming is a coherent type of interference. As this interference is injected through the main lobe of the antenna into a radar system, the interference heavily degrades the performance of the radar system. In this paper, we propose an anti-jamming method based on minimum variance distortionless response (MVDR) that estimates a covariance matrix by obtaining smallsample pure jamming signals through jamming recognition. Time-frequency analysis is performed in the one-dimensional range profile of the pulse-compressed radar echo, and the snapshot sampling of pure jamming is achieved by searching the range gates for the target and the jamming in a two-dimensional range-frequency graph considering the time-frequency differences between the target and jamming signals. Assuming that the available data of snapshot sampling are insufficient, a covariance matrix for pure jamming is reconstructed through an iterative adaptive approach (IAA) and used as the training sample for the MVDR beamformer to suppress main-lobe interrupted-sampling repeater jamming. Finally, the method is validated by comparing the simulation results with the measured results.

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Section: B Jamming Suppression Based On Iaamentioning

confidence: 99%

Section: B Jamming Suppression Based On Iaamentioning

confidence: 99%

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Suppression Method for Main-Lobe Interrupted Sampling Repeater Jamming in Distributed Radar

Chen

Zhang

et al. 2020

IEEE Access

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“…However, in the forward-looking case, monostatic SAR cannot achieve high-resolution imaging along the azimuth direction because it cannot form an effective Doppler bandwidth, and mirror effects also occur in this scenario. To solve these difficulties, bistatic forward-looking SAR (BFSAR) has been introduced as a working mode, in which the receiver adopts forward-looking and spotlight reception while the transmitter adopts broadside or squint illumination to simultaneously form an effective Doppler bandwidth and avoid mirror effects [3][4][5][6][7][8][9][10][11]. On the other hand, mini unmanned aerial vehicles (mini-UAVs) have been adopted by radar engineers as the carriers of SAR due to their flexibility and ease of deployment, especially for some new applications such as aircraft self-landing, material airdrops, terrain awareness and avoidance [12].…”

Section: Introductionmentioning

confidence: 99%

An Improved Frequency-Domain Image Formation Algorithm for Mini-UAV-Based Forward-Looking Spotlight BiSAR Systems

et al. 2020

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Mini-unmanned aerial vehicle (UAV)-based bistatic forward-looking synthetic aperture radar (SAR) (mini-UAV-based BFSAR) is much more attractive than the monostatic one because of the flexibility of the system geometry selection as well as its simplicity of system operation, especially with the mini-UAV platform. However, the trajectory of the mini-UAV needs to be accurately modeled since it is very sensitive to the external environment, and the forward-looking configuration results in more severe spatial variance in image formation processing. In the paper, an improved frequency-domain imaging algorithm based on a very accurate slant range model is proposed for mini-UAV-based BFSAR with spotlight illumination. First, a more accurate slant range expression considering the motion characteristics of the UAV and bistatic spotlight configuration is re-derived. Second, a new range nonlinear chirp scaling (NLCS) operator was derived based on the accurate bistatic slant range model. Third, an improved azimuth NLCS operator in the Doppler frequency domain was established for the spotlight illumination of the transmitter and receiver in mini-UAV based BFSAR systems. Finally, the proposed algorithm is validated by both simulations and real datasets.

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A radar waveform bandwidth selection strategy for wideband tracking

Cited by 2 publications

References 3 publications

Suppression Method for Main-Lobe Interrupted Sampling Repeater Jamming in Distributed Radar

Suppression Method for Main-Lobe Interrupted Sampling Repeater Jamming in Distributed Radar

An Improved Frequency-Domain Image Formation Algorithm for Mini-UAV-Based Forward-Looking Spotlight BiSAR Systems

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