A deceptive pull-off jamming method to terminal guidance radar is put forward in this paper.The design rules about the important jamming parameters are discussed in detail,including the number of the decoy targets in ...A deceptive pull-off jamming method to terminal guidance radar is put forward in this paper.The design rules about the important jamming parameters are discussed in detail,including the number of the decoy targets in range dimension,the velocity of the range gate pull-off,and the number of the decoy targets in velocity dimension and the velocity of the Doppler frequency pull-off.Also,the steps to design these parameters are brought out.The rules and design procedure discussed in this paper have important meaning for the choice of the reasonable jamming parameters in the practical applications,which can help to obtain good jamming effect.展开更多
Multi-range-false-target(MRFT) jamming is particularly challenging for tracking radar due to the dense clutter and the repeated multiple false targets. The conventional association-based multi-target tracking(MTT) met...Multi-range-false-target(MRFT) jamming is particularly challenging for tracking radar due to the dense clutter and the repeated multiple false targets. The conventional association-based multi-target tracking(MTT) methods suffer from high computational complexity and limited usage in the presence of MRFT jamming.In order to solve the above problems, an efficient and adaptable probability hypothesis density(PHD) filter is proposed. Based on the gating strategy, the obtained measurements are firstly classified into the generalized newborn target and the existing target measurements. The two categories of measurements are independently used in the decomposed form of the PHD filter. Meanwhile,an amplitude feature is used to suppress the dense clutter. In addition, an MRFT jamming suppression algorithm is introduced to the filter. Target amplitude information and phase quantization information are jointly used to deal with MRFT jamming and the clutter by modifying the particle weights of the generalized newborn targets. Simulations demonstrate the proposed algorithm can obtain superior correct discrimination rate of MRFT, and high-accuracy tracking performance with high computational efficiency in the presence of MRFT jamming in the dense clutter.展开更多
基金Sponsored by National Basic Research Program of China (6139001012)
文摘A deceptive pull-off jamming method to terminal guidance radar is put forward in this paper.The design rules about the important jamming parameters are discussed in detail,including the number of the decoy targets in range dimension,the velocity of the range gate pull-off,and the number of the decoy targets in velocity dimension and the velocity of the Doppler frequency pull-off.Also,the steps to design these parameters are brought out.The rules and design procedure discussed in this paper have important meaning for the choice of the reasonable jamming parameters in the practical applications,which can help to obtain good jamming effect.
基金supported by the National Natural Science Foundation of China (11472214)。
文摘Multi-range-false-target(MRFT) jamming is particularly challenging for tracking radar due to the dense clutter and the repeated multiple false targets. The conventional association-based multi-target tracking(MTT) methods suffer from high computational complexity and limited usage in the presence of MRFT jamming.In order to solve the above problems, an efficient and adaptable probability hypothesis density(PHD) filter is proposed. Based on the gating strategy, the obtained measurements are firstly classified into the generalized newborn target and the existing target measurements. The two categories of measurements are independently used in the decomposed form of the PHD filter. Meanwhile,an amplitude feature is used to suppress the dense clutter. In addition, an MRFT jamming suppression algorithm is introduced to the filter. Target amplitude information and phase quantization information are jointly used to deal with MRFT jamming and the clutter by modifying the particle weights of the generalized newborn targets. Simulations demonstrate the proposed algorithm can obtain superior correct discrimination rate of MRFT, and high-accuracy tracking performance with high computational efficiency in the presence of MRFT jamming in the dense clutter.
