Range-Ambiguous Sea Clutter Suppression for Multichannel Spaceborne Radar Applications Via Alternating APC Processing

Huang, Penghui; Yang, Hao; Zou, Zihao; Xia, Xiang-Gen; Liao, Guisheng; Zhang, Yuhong

doi:10.1109/taes.2023.3281305

Cited by 12 publications

(2 citation statements)

References 46 publications

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“…Radar can better obtain information and optimize target detection performance. It is mainly divided into frequency division, time division and code division in terms of the technical implementation [20][21][22][23]. By introducing the DOFs of the transmitting dimension, the transmitting dimension, jointly with the receiving dimension, distance dimension, Doppler dimension and polarization dimension, can improve the flexibility of radar system resources, and the new method of multi-dimensional domain signal processing is the main development direction of future radar to obtain target information.…”

Section: Introductionmentioning

confidence: 99%

A Novel Non-Stationary Clutter Suppression Approach for Space-Based Early Warning Radar Using an Interpulse Multi-Frequency Mode

Qiao,

Zhang,

Zhang

et al. 2024

Remote Sensing

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The non-stationary clutter of space-based early warning radar (SBEWR) is more serious than that of airborne early warning radar. This phenomenon is primarily attributed to the Earth’s rotation and range ambiguity. The increase in clutter degrees of freedom (DOFs) and the significant widening of the clutter suppression notch are not conducive to moving target detection near main lobe clutter. This paper proposes an effective approach to suppress non-stationary clutter based on an interpulse multi-frequency mode for SBEWR. Using the orthogonality of the uniform stepping frequency signal, partial range ambiguity can be effectively suppressed, and the clutter DOFs will be reduced. Subsequently, joint pitch-azimuth-Doppler three-dimensional spacetime adaptive processing and slant range preprocessing are used to perform clutter suppression. This combination not only curtails the estimation error associated with the clutter covariance matrix but also enhances the overall detection capabilities of the system. The simulation results verify the effectiveness of the proposed approach.

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Section: Introductionmentioning

confidence: 99%

A Novel Non-Stationary Clutter Suppression Approach for Space-Based Early Warning Radar Using an Interpulse Multi-Frequency Mode

Qiao,

Zhang,

Zhang

et al. 2024

Remote Sensing

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show abstract

“…Understanding the characteristics of sea clutter is crucial for designing effective radar target-detection algorithms. The statistical properties of sea clutter play a significant role in determining the constant false alarm characteristics of target detection [1][2][3]. Specifically, the collected sea clutter data from shore-based radar exhibits a pronounced long trailing behavior in its statistical distribution [4][5][6][7][8], commonly referred to as the phenomenon of heavy trailing.…”

Section: Introductionmentioning

confidence: 99%

Enhanced Particle Swarm Optimization Algorithm for Sea Clutter Parameter Estimation in Generalized Pareto Distribution

Yang,

2023

Applied Sciences

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Accurate parameter estimation is essential for modeling the statistical characteristics of ocean clutter. Common parameter estimation methods in generalized Pareto distribution models have limitations, such as restricted parameter ranges, lack of closed-form expressions, and low estimation accuracy. In this study, the particle swarm optimization (PSO) algorithm is used to solve the non-closed-form parameter estimation equations of the generalized Pareto distribution. The goodness-of-fit experiments show that the PSO algorithm effectively solves the non-closed parameter estimation problem and enhances the robustness of fitting the generalized Pareto distribution to heavy-tailed oceanic clutter data. In addition, a new parameter estimation method for the generalized Pareto distribution is proposed in this study. By using the difference between the statistical histogram of the data and the probability density function/cumulative distribution function of the generalized Pareto distribution as the target, an adaptive function with weighted coefficients is constructed to estimate the distribution parameters. A hybrid PSO (HPSO) algorithm is used to search for the best position of the fitness function to achieve the best parameter estimation of the generalized Pareto distribution. Simulation analysis shows that the HPSO algorithm outperforms the PSO algorithm in solving the parameter optimization task of the generalized Pareto distribution. A comparison with other traditional parameter estimation methods for generalized Pareto distribution shows that the HPSOHPSO algorithm exhibits strong parameter estimation performance, is efficient and stable, and is not limited by the parameter range.

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Reduced-dimension STAP method for conformal array based on sequential convex programming

Shi,

Yao,

Wang

et al. 2025

Signal Processing

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Range-Ambiguous Sea Clutter Suppression for Multichannel Spaceborne Radar Applications Via Alternating APC Processing

Cited by 12 publications

References 46 publications

A Novel Non-Stationary Clutter Suppression Approach for Space-Based Early Warning Radar Using an Interpulse Multi-Frequency Mode

A Novel Non-Stationary Clutter Suppression Approach for Space-Based Early Warning Radar Using an Interpulse Multi-Frequency Mode

Enhanced Particle Swarm Optimization Algorithm for Sea Clutter Parameter Estimation in Generalized Pareto Distribution

Reduced-dimension STAP method for conformal array based on sequential convex programming

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