Jamming suppression is traditionally achieved through the use of spatial filters based on array signal processing theory.In order to achieve better jamming suppression performance,many studies have applied blind sourc...Jamming suppression is traditionally achieved through the use of spatial filters based on array signal processing theory.In order to achieve better jamming suppression performance,many studies have applied blind source separation(BSS)to jamming suppression.BSS can achieve the separation and extraction of the individual source signals from the mixed signal received by the array.This paper proposes a perspective to recognize BSS as spatial band-pass filters(SBPFs)for jamming suppression applications.The theoretical derivation indicates that the processing of mixed signals by BSS can be perceived as the application of a set of SBPFs that gate the source signals at various angles.Simulations are performed using radar jamming suppression as an example.The simulation results suggest that BSS and SBPFs produce approximately the same effects.Simulation results are consistent with theoretical derivation results.展开更多
To correct the range walk through resolution cell in Doppler beam sharpening （DBS） imaging, a new DBS imaging algorithm based on Keystone transform is proposed. Without the exact values of the movement parameters an...To correct the range walk through resolution cell in Doppler beam sharpening （DBS） imaging, a new DBS imaging algorithm based on Keystone transform is proposed. Without the exact values of the movement parameters and the look angle of the radar platform in the multi-targets environment, a linear trans- form on the received data is employed to correct different range walk values accurately under the condition of Doppler frequency ambiguity in this algorithm. This method can realize the cohe- rent integration in azimuth dimension and improve the azimuth resolution. In order to reduce the computational burden, a fast implementation of Keystone transform is used. Theoretical anal- ysis and simulation results demonstrate the effectiveness of the new algorithm. And through comparing the computational load of the fast implementation with several other algorithms, the real-time processing ability of the proposed algorithm is superior to that of other algorithms.展开更多
基金supported by the National Natural Science Foundation of China(6237104662201048)the Natural Science Foundation of Chongqing,China(cstc2020jcyj-msxmX0260).
文摘Jamming suppression is traditionally achieved through the use of spatial filters based on array signal processing theory.In order to achieve better jamming suppression performance,many studies have applied blind source separation(BSS)to jamming suppression.BSS can achieve the separation and extraction of the individual source signals from the mixed signal received by the array.This paper proposes a perspective to recognize BSS as spatial band-pass filters(SBPFs)for jamming suppression applications.The theoretical derivation indicates that the processing of mixed signals by BSS can be perceived as the application of a set of SBPFs that gate the source signals at various angles.Simulations are performed using radar jamming suppression as an example.The simulation results suggest that BSS and SBPFs produce approximately the same effects.Simulation results are consistent with theoretical derivation results.
基金supported by the Basic Research of the National Department of Defense (A2220060054)the Foundation of Shanghai Aerospace Science and Technology
文摘To correct the range walk through resolution cell in Doppler beam sharpening （DBS） imaging, a new DBS imaging algorithm based on Keystone transform is proposed. Without the exact values of the movement parameters and the look angle of the radar platform in the multi-targets environment, a linear trans- form on the received data is employed to correct different range walk values accurately under the condition of Doppler frequency ambiguity in this algorithm. This method can realize the cohe- rent integration in azimuth dimension and improve the azimuth resolution. In order to reduce the computational burden, a fast implementation of Keystone transform is used. Theoretical anal- ysis and simulation results demonstrate the effectiveness of the new algorithm. And through comparing the computational load of the fast implementation with several other algorithms, the real-time processing ability of the proposed algorithm is superior to that of other algorithms.
