Only in the presence of sidelobe jamming （SLJ）, can the conventional adaptive monopulse technique null the jamming effectively and maintain the monopulse angle estimation accuracy simultaneously. While mainlobe jamm...Only in the presence of sidelobe jamming （SLJ）, can the conventional adaptive monopulse technique null the jamming effectively and maintain the monopulse angle estimation accuracy simultaneously. While mainlobe jamming （MLJ） exists, the mainlobe of adaptive pattern will subject to serious distortion, which results in a failure of detecting and tracking targets by monopulse technique. Therefore, a monopulse angle estimation algorithm based on combining sum-difference beam and auxiliary beam is presented. This algorithm utilizes both high gain difference beams and high gain auxiliary beams for cancelling the mainlobe jammer and multiple sidelobe jammers （SLJs） while keeping an adap- tive monopulse ratio. Theoretical analysis and simulation results indicate that the serious invalidation of monopulse technique in MLJ and SLJs scenarios is resolved well, which improves the monopulse angle accuracy greatly. Furthermore, the proposed algorithm is of simple implementation and low computational complexity.展开更多
A new recursive algorithm with the partial parallel structure based on the linearly constrained minimum variance(LCMV)criterion for adaptive monopulse systems is proposed.The weight vector associated with the original...A new recursive algorithm with the partial parallel structure based on the linearly constrained minimum variance(LCMV)criterion for adaptive monopulse systems is proposed.The weight vector associated with the original whole antenna array is decomposed into several adaptive weight sub-vectors firstly.An adaptive algorithm based on the conventional LCMV principle is then deduced to update the weight sub-vectors for sum and difference beam,respectively.The optimal weight vector can be obtained after convergence.The required computational complexity is evaluated for the proposed technique,which is on the order of O(N)and less than that of the conventional LCMV method.The flow chart scheme with the partial parallel structure of the proposed algorithm is introduced.This scheme is easy to be implemented on a distributed computer/digital signal processor(DSP)system to solve the problems of the heavy computational burden and vast data transmission of the large-scale adaptive monopulse array.Then,the monopulse ratio and convergence rate of the proposed algorithm are evaluated by numerical simulations.Compared with some recent adaptive monopulse estimation methods,a better performance on computational complexity and monopulse ratio can be achieved with the proposed adaptive method.展开更多
基金supported by the National Natural Science Foundation of China(60925005)
文摘Only in the presence of sidelobe jamming （SLJ）, can the conventional adaptive monopulse technique null the jamming effectively and maintain the monopulse angle estimation accuracy simultaneously. While mainlobe jamming （MLJ） exists, the mainlobe of adaptive pattern will subject to serious distortion, which results in a failure of detecting and tracking targets by monopulse technique. Therefore, a monopulse angle estimation algorithm based on combining sum-difference beam and auxiliary beam is presented. This algorithm utilizes both high gain difference beams and high gain auxiliary beams for cancelling the mainlobe jammer and multiple sidelobe jammers （SLJs） while keeping an adap- tive monopulse ratio. Theoretical analysis and simulation results indicate that the serious invalidation of monopulse technique in MLJ and SLJs scenarios is resolved well, which improves the monopulse angle accuracy greatly. Furthermore, the proposed algorithm is of simple implementation and low computational complexity.
基金supported by the National Natural Science Foundation of China(11273017)
文摘A new recursive algorithm with the partial parallel structure based on the linearly constrained minimum variance(LCMV)criterion for adaptive monopulse systems is proposed.The weight vector associated with the original whole antenna array is decomposed into several adaptive weight sub-vectors firstly.An adaptive algorithm based on the conventional LCMV principle is then deduced to update the weight sub-vectors for sum and difference beam,respectively.The optimal weight vector can be obtained after convergence.The required computational complexity is evaluated for the proposed technique,which is on the order of O(N)and less than that of the conventional LCMV method.The flow chart scheme with the partial parallel structure of the proposed algorithm is introduced.This scheme is easy to be implemented on a distributed computer/digital signal processor(DSP)system to solve the problems of the heavy computational burden and vast data transmission of the large-scale adaptive monopulse array.Then,the monopulse ratio and convergence rate of the proposed algorithm are evaluated by numerical simulations.Compared with some recent adaptive monopulse estimation methods,a better performance on computational complexity and monopulse ratio can be achieved with the proposed adaptive method.
